State information acquisition method and related apparatus

Abstract

A state information acquisition method and a related apparatus, which are applied to the technical field of detection. The present application can integrate channel data of a detection apparatus within a certain time period, so as to sense and assess anomalies in the channel state of the detection apparatus, thereby effectively monitoring channels of the detection apparatus. Moreover, the present application can identify anomalies in the channel state of the detection apparatus during a period of the life cycle of the detection apparatus, thereby facilitating the timely discovery of an abnormal channel state of the detection apparatus, and ensuring the sensing reliability of the detection apparatus. In particular, in a scenario where a detection apparatus is arranged in a vehicle, detection results of the detection apparatus are typically used for intelligent functions of the vehicle, such as an intelligent driving system, an autonomous driving system and an automatic parking system. Using the solution of the present application can ensure the reliability of the intelligent functions of the vehicle, thereby improving the riding safety of users.

Description

Status information acquisition method and related devices Technical Field

[0001] This application relates to the field of detection technology, and in particular to methods and devices for acquiring status information. Background Technology

[0002] With the development of detection technology, more and more detection devices are being widely used in scenarios such as detection, target recognition, and positioning, bringing great convenience to people's lives and travel. Detection devices can generate transmitted signals and receive the return signals (i.e., echoes) from the object space, and based on the return signals, information about targets in the object space can be obtained. When detection devices are installed on electronic devices (such as vehicles, logistics robots, etc.), they can act as the "eyes" for perceiving the environment, enabling the detection of the surrounding environment of the electronic devices. As the intelligence level of electronic devices increases, the requirements for the detection capabilities of these devices are also increasing.

[0003] Detection devices typically include multiple channels, and the channel status of the detection device may change with use. This change cannot be measured before leaving the factory and cannot be detected by routine hardware self-tests. In severe cases, it can lead to a significant decrease in the angle measurement capability of the detection device, affecting its detection ability.

[0004] Therefore, how to effectively obtain the impact of abnormal channel characteristics caused by the use of the detection device on the detection capability of the detection device and respond in a timely manner to ensure detection performance is a hot topic of research for those skilled in the art. Summary of the Invention

[0005] This application provides a method and related apparatus for obtaining status information, which can comprehensively detect and evaluate the abnormality of the channel status of the detection device by integrating the channel data of the detection device within a certain time period. It can effectively monitor the channel of the detection device, help to detect abnormal channel status of the detection device in a timely manner, and ensure the reliability of the detection device's sensing.

[0006] Firstly, this application provides a method for acquiring status information, which can be executed by a processing device or a component (such as a chip or module) within the processing device. This method is used to manage a detection device; executively, the detection device can be radar or lidar. Optionally, the processing device can be a controller or server, such as a microcontroller unit (MCU) or an intelligent driving domain controller (hereinafter referred to as a domain controller). For ease of description, the following description uses the processing device as the executing entity of this method, and the processing device managing a first detection device as an example. In actual implementation, the executing entity of this method can be named in other ways.

[0007] The method for obtaining status information includes: acquiring channel data of the first detection device, and determining the status information of the first detection device based on the channel data. Specifically, the channel data of the first detection device is used to indicate the channel characteristics of the first detection device within a first time period, and the status information is used to indicate whether the channel status of the first detection device is abnormal.

[0008] The first time period is a predefined or set time period. For example, the first time period can be the time period between the manufacturing time of the detection device and the current time.

[0009] In the above scheme, the processing device can comprehensively analyze the channel data of the detection device within a certain time period to perceive and assess anomalies in the channel status of the detection device, effectively monitoring the channels of the detection device. Furthermore, the processing device can identify anomalies in the channel status of the detection device throughout its entire lifecycle, helping to promptly detect abnormal channel states and ensuring the reliability of the detection device's sensing capabilities. For example, if the first time period is from the time the first detection device was manufactured to the current time, the processing device can monitor the channel status throughout the entire lifecycle of the detection device, improving its reliability.

[0010] Especially in scenarios where the detection device is installed in a vehicle, the detection results are typically used for the vehicle's intelligent functions, such as intelligent driving systems, autonomous driving systems, and automatic parking systems. Utilizing the solution in this application can ensure the reliability of the vehicle's intelligent functions and improve user safety while riding in the vehicle.

[0011] In one possible implementation of the first aspect, the channel data of the first detection device includes characteristic data corresponding to the target point collected by the first detection device through the channel during a first time period, and the characteristic data includes amplitude and / or phase.

[0012] When there is a large measurement deviation in amplitude and / or phase, it indicates a significant decrease in the angle measurement capability of the detection device, thus affecting its detection capability. In the above embodiment, the channel data includes the amplitude and / or phase corresponding to the target point. The processing device can determine whether the channel status of the detection device is abnormal based on the amplitude and / or phase, which helps to detect abnormal channel status of the detection device in a timely manner, improves the accuracy of abnormality judgment, and ensures the reliability of the detection device's sensing.

[0013] In another possible implementation of the first aspect, the method can be applied to a server connected to the first control device to obtain channel data of the first detection device, including: obtaining channel data from the first detection device connected to the first control device.

[0014] In the above embodiments, channel data is added to the uplink interface from the first detection device to the first control device and the uplink interface from the first control device to the server, so that the server can subsequently evaluate the channel status of the detection device based on the channel data.

[0015] In another possible implementation of the first aspect, the method further includes: sending status information to the first control device.

[0016] In the above embodiments, status information is added to the downlink interface from the server to the first control device so that users can understand the channel status of the first detection device in a timely manner.

[0017] In another possible implementation of the first aspect, the status information includes anomaly alarm information and / or calibration parameters. The anomaly alarm information indicates an anomaly in the channel status of the first detection device, and the calibration parameters indicate an anomaly in the channel status of the first detection device and are used to calibrate the channels of the first detection device.

[0018] For example, calibration parameters can reduce the deviation between the channel data of the first detection device and normal data to fall within a first value range. For instance, the first value range is a pre-set acceptable range; for example, the acceptable range for phase data could be -0.5 degrees to +0.5 degrees. The above implementation can reduce the impact of abnormal channel characteristics on the detection capability of the detection device, improve the detection accuracy of the detection device, and ensure the reliability of the detection device's sensing.

[0019] In another possible implementation of the first aspect, determining the status information of the first detection device based on the channel data of the first detection device includes: determining the status information of the first detection device based on the channel data of the first detection device and the channel data of at least two second detection devices. The channel data of the at least two second detection devices are used to indicate the channel characteristics of the at least two second detection devices within a first time period, and the at least two second detection devices are of the same model as the first detection device.

[0020] In the above embodiments, the processing device integrates channel data from multiple detection devices and uses horizontal comparison of channel data to perceive and evaluate abnormalities in the channel status of the detection devices. This effectively monitors the channels of the detection devices, improves the accuracy of abnormality judgment, and ensures the reliability of the detection devices' perception.

[0021] In another possible implementation of the first aspect, the method is applied to a server connected to a second control device, and the method further includes: acquiring channel data from a third detection device connected to the second control device. The channel data from the third detection device is used to indicate the channel characteristics of the third detection device during a second time period, the second time period including the first time period, and the third detection device belonging to at least two second detection devices.

[0022] Optionally, the server connected to the second control device may be the same server as the server connected to the first control device, and the server may connect to multiple control devices.

[0023] In the above embodiments, channel data is added to the uplink interface from the third detection device to the second control device and the uplink interface from the second control device to the server, so that the server can evaluate the channel status of the detection device based on the channel data.

[0024] In another possible implementation of the first aspect, determining the status information of the first detection device based on the channel data of the first detection device and the channel data of at least two second detection devices includes: determining the status information of the first detection device based on the changes in the channel characteristics of the first detection device during a first time period and the changes in the channel characteristics of the at least two second detection devices during the first time period.

[0025] In the above embodiments, the processing device can perceive and evaluate the abnormality of the channel status of the detection devices by making a horizontal comparison based on the changes in the channel characteristics of multiple detection devices over time. This can effectively monitor the channels of the detection devices, improve the accuracy of judging abnormalities, and ensure the reliability of the detection devices' perception.

[0026] In another possible implementation of the first aspect, when the deviation between the change in the channel characteristics of the first detection device during a first time period and the changes in the channel characteristics of at least two second detection devices during the first time period satisfies a predefined abnormality condition, the status information is used to indicate an abnormal channel status of the first detection device.

[0027] In another possible implementation of the first aspect, the abnormal conditions include abrupt abnormal conditions and non-abrupt abnormal conditions, wherein the abrupt abnormal conditions indicate that the change in the channel characteristics of the first detection device during the first time period deviates abruptly from the change in the channel characteristics of at least two second detection devices during the first time period.

[0028] In another possible implementation of the first aspect, the anomalous mutation condition includes: the difference between the maximum deviation data and the minimum deviation data is greater than a second threshold. Wherein, the maximum deviation data is the maximum value of the difference between the channel data of the first detection device and the channel data of at least two second detection devices within the second sub-time period, and the minimum deviation data is the minimum value of the difference between the channel data of the first detection device and the channel data of at least two second detection devices within the second sub-time period, wherein the second sub-time period belongs to the first time period.

[0029] The second threshold is a pre-set or pre-defined difference threshold. When the deviation data of the detection device in the second sub-time period exceeds the second threshold, it can be considered that the detection device suddenly deviates during this time period, and the deviation change is large, which is a sudden anomaly. Since the channel state anomaly caused by the deformation of the detection device due to external forces is usually sudden, the above implementation method can determine whether the sudden anomaly condition is met based on the channel data of the detection device. Therefore, the above implementation method can identify the channel state anomaly caused by the deformation of the detection device due to external forces, effectively monitor the channel of the detection device, and ensure the reliability of the detection device's sensing.

[0030] In another possible implementation of the first aspect, the non-mutation anomaly condition includes a gradual anomaly condition and a sustained deviation condition. The gradual anomaly condition indicates that the change in the channel characteristics of the first detection device within a first time period gradually deviates from the changes in the channel characteristics of at least two second detection devices within the same first time period. The sustained deviation condition indicates that the change in the channel characteristics of the first detection device within the first time period continuously deviates from the changes in the channel characteristics of at least two second detection devices within the same first time period.

[0031] In another possible implementation of the first aspect, the gradual anomaly condition includes: the difference between the maximum deviation data and the minimum deviation data is greater than a first threshold and less than a second threshold. The maximum deviation data and the minimum deviation data are as described above.

[0032] The second threshold is described above, and the first threshold is a pre-set or pre-defined difference threshold. When the deviation data of the detection device in the second sub-time period is greater than the first threshold but less than the second threshold, it can be considered that the detection device has deviated during this time period, and the deviation change is small, which is a gradual anomaly. Since the channel state anomalies caused by dirt / aging of the detection device are usually slow changes, the above implementation can determine whether the gradual anomaly condition is met based on the channel data of the detection device. Therefore, the above implementation can identify the channel state anomalies caused by dirt / aging of the detection device, effectively monitor the channel of the detection device, and ensure the reliability of the detection device's sensing.

[0033] In another possible implementation of the first aspect, the persistent deviation condition includes: the difference between the maximum deviation data and the minimum deviation data is less than a first threshold. The maximum and minimum deviation data are as described above.

[0034] The first threshold is as described above. When the deviation data of the detection device in the second sub-time period is less than the first threshold, it can be considered that the detection device has deviated during this time period, and the deviation change is very small (e.g., the deviation does not change significantly over time), which is a continuous deviation anomaly. Since the channel state anomaly caused by the large difference between the module operating conditions inside the detection device and the standard operating conditions when the equipment is tabulated (e.g., voltage, temperature, humidity, etc.) is usually stable but continuously deviating, the above implementation can determine whether the continuous deviation condition is met based on the channel data of the detection device. Thus, the above implementation can identify the channel state anomaly caused by the large difference between the module operating conditions inside the detection device and the standard operating conditions when the equipment is tabulated (e.g., voltage, temperature, humidity, etc.), effectively monitor the channel of the detection device, and ensure the reliability of the detection device's sensing.

[0035] In another possible implementation of the first aspect, when the change in the channel characteristics of the first detection device during a first sub-time period deviates from the change in the channel characteristics of the first detection device during other sub-time periods, the status information is used to indicate an abnormal channel status of the first detection device. The first time period includes multiple sub-time periods, and the first sub-time period belongs to multiple sub-time periods; the other sub-time periods are at least two sub-time periods other than the first sub-time period.

[0036] In the above embodiments, the processing device can perceive and evaluate the abnormality of the channel state of the detection device by comparing changes in channel characteristics across multiple sub-time periods within the first time period, based on channel data from the detection device. This effectively monitors the channels of the detection device. Furthermore, if the first time period is the time between the manufacturing time of the first detection device and the current time, the processing device can perceive and evaluate the abnormality of the channel state of the detection device based on the characteristic changes of the detection device throughout its entire life cycle. This helps to promptly detect abnormal channel states of the detection device and ensures the reliability of the detection device's perception.

[0037] Secondly, this application provides another method for acquiring status information, which can be executed by a processing device or a component (such as a chip or module) within the processing device. This method is used to manage detection devices for a specific product batch; executively, the detection device can be a radar or lidar. Optionally, the processing device can be a controller or a server, such as an MCU or a domain controller. For ease of description, the following explanation uses the processing device as the executing entity of this method, and the processing device managing detection devices belonging to the first product batch as an example. In actual implementation, the executing entity of this method can be named differently.

[0038] The method for obtaining status information includes: acquiring channel data of the detection devices belonging to the first product batch, and determining status information based on the channel data of the detection devices belonging to the first product batch. Specifically, the channel data of the detection devices belonging to the first product batch is used to indicate the channel characteristics of the detection devices belonging to the first product batch within a first time period, and the status information is used to indicate whether the channel status of the detection devices belonging to the first product batch is abnormal.

[0039] The first time period is a predefined or set time period. For example, the first time period can be the time period between the manufacturing time of the detection device and the current time.

[0040] A product batch can be defined as a collection of products manufactured under the same time, process conditions, and raw materials during the production process. For example, products of the same model produced within the same time period using the same production line and process constitute a product batch. For instance, 500 detectors of the same model produced by a detection device manufacturing plant between January 1st and January 15th using the same raw materials, production line, and process constitute a product batch.

[0041] In the above scheme, the processing device can determine whether the channel status of the detection devices belonging to the first product batch is abnormal based on the channel data of the detection devices belonging to the first product batch. It can effectively monitor the channels of the entire batch of detection devices and help to provide early warning of potential network problems.

[0042] In one possible implementation of the second aspect, the method is applied to a server connected to a management device, and the method further includes sending status information to the management device.

[0043] The management device is a device with communication capabilities. Optionally, the management device may be the device used by the manufacturer of the detection devices belonging to the first product batch. Optionally, after receiving status information, the personnel using the management device can determine a solution strategy for channel status anomalies of the detection devices belonging to the first product batch based on the status information, such as recalling all detection devices belonging to the first product batch.

[0044] In one possible implementation of the second aspect, the channel data of the detection device belonging to the first product batch includes characteristic data corresponding to the target point collected by the detection device belonging to the first product batch through the channel in the first time period, and the characteristic data includes amplitude and / or phase.

[0045] When there is a large measurement deviation in amplitude and / or phase, it indicates a significant decrease in the angle measurement capability of the detection device, thus affecting its detection capability. In the above embodiment, the channel data includes the amplitude and / or phase corresponding to the target point. The processing device can determine whether the channel status of the detection device belonging to the first product batch is abnormal based on the amplitude and / or phase. This helps to detect abnormal channel status of the detection device in a timely manner, improves the accuracy of abnormality judgment, and ensures the reliability of the detection device's sensing.

[0046] In another possible implementation of the second aspect, determining status information based on channel data of the detection devices belonging to the first product batch includes: determining status information based on channel data of the detection devices belonging to the first product batch and channel data of the detection devices belonging to the second product batch. The channel data of the detection devices belonging to the second product batch is used to indicate the channel characteristics of the detection devices belonging to the second product batch within a first time period. The detection devices belonging to the second product batch have the same model as the detection devices belonging to the first product batch but are from different batches. Optionally, the channel data of the detection devices belonging to the second product batch includes characteristic data corresponding to the target point collected by the detection devices belonging to the second product batch through the channel within the first time period, and the characteristic data includes amplitude and / or phase.

[0047] In the above embodiments, the processing device integrates the channel data of the detection devices from different product batches and compares the channel data horizontally to perceive and evaluate the abnormalities in the channel status of the detection devices belonging to the first product batch. This can effectively monitor the channels of the entire batch of detection devices, improve the accuracy of abnormality judgment, and help to provide early warning of potential network problems.

[0048] In another possible implementation of the second aspect, determining status information based on channel data of the detection device belonging to the first product batch and channel data of the detection device belonging to the second product batch includes: determining status information based on changes in channel characteristics of the detection device belonging to the first product batch during a first time period and changes in channel characteristics of the detection device belonging to the second product batch during the first time period.

[0049] In another possible implementation of the second aspect, when the channel characteristics of the detection device belonging to the first product batch deviate from the channel characteristics of the detection device belonging to the second product batch within the first time period, the status information is used to indicate that the channel status of the detection device belonging to the first product batch is abnormal.

[0050] In the above embodiments, the processing device can monitor the differences in channel characteristics of detection devices among different product batches, obtain the overall performance trend of detection devices in different batches, effectively monitor the channels of the entire batch of detection devices, improve the accuracy of anomaly judgment, and help to provide early warning of potential network problems.

[0051] Thirdly, this application provides another method for acquiring status information, which can be executed by a control device or a component (such as a chip or module) connected to the first detection device. Exemplarily, the detection device can be a radar or lidar. The control device can be an MCU, a domain controller, etc. For ease of description, the following explanation uses the control device as the executing entity of this method, with the control device managing the first detection device as an example. In actual implementation, the executing entity of this method can be other names.

[0052] The status information acquisition method includes: acquiring channel data from the first detection device, sending the channel data from the first detection device to the server, receiving status information from the server, and sending status information to the first detection device. The channel data from the first detection device is used to indicate the channel characteristics of the first detection device within a first time period, and the status information is used to indicate whether the channel status of the first detection device is abnormal.

[0053] In the above scheme, channel data is added to the uplink interface from the first detection device to the control device and the uplink interface from the control device to the server, so that the server can evaluate the channel status of the first detection device based on the channel data. Status information is added to the downlink interface from the server to the control device and the downlink interface from the control device to the first detection device, so that the user can understand the channel status of the first detection device in a timely manner and calibrate the channel of the first detection device.

[0054] In one possible implementation of the third aspect, the channel data of the first detection device includes characteristic data corresponding to the target point collected by the first detection device through the channel during a first time period, and the characteristic data includes amplitude and / or phase.

[0055] In another possible implementation of the third aspect, the status information includes anomaly alarm information and / or calibration parameters. The anomaly alarm information is used to indicate an anomaly in the channel status of the first detection device, and the calibration parameters are used to indicate an anomaly in the channel status of the first detection device and to calibrate the channel of the first detection device.

[0056] In another possible implementation of the third aspect, acquiring the channel data of the first detection device includes: receiving the channel data of the first detection device reported by the first detection device.

[0057] In another possible implementation of the third aspect, acquiring the channel data of the first detection device includes: receiving candidate channel data of the first detection device reported by the first detection device, and determining the channel data of the first detection device based on the candidate channel data. The candidate channel data includes characteristic data corresponding to candidate points collected by the first detection device through the channel within a first time period, and the target point is a candidate point among the candidate points that meets a preset first condition.

[0058] In the above embodiments, after the control device receives the candidate channel data of the first detection device reported by the first detection device, it can perform filtering to obtain the target point from the candidate points, thereby reducing the amount of channel data of the first detection device, reducing the subsequent data processing time, and improving the efficiency of judging whether the channel status of the detection device is abnormal.

[0059] In yet another possible implementation of the third aspect, the first condition includes at least one of the following:

[0060] The number of target objects in the point cloud meets preset quantity conditions and / or preset distance conditions, and the acquisition scene when the point cloud is acquired meets preset scene conditions. The preset distance condition is used to constrain the distance between the target objects and the first detection device. The point cloud includes multiple candidate points.

[0061] In another possible implementation of the third aspect, the number of target objects in the point cloud satisfies a preset quantity condition and / or a preset distance condition, including: the target objects in the point cloud are isolated target objects and the isolated target objects are located within a first distance range.

[0062] Fourthly, this application provides yet another method for acquiring status information, which can be executed by a detection device connected to a control device or a component (such as a chip or module) within the detection device. Exemplarily, the detection device can be a radar or a lidar. For ease of description, the following explanation uses the first detection device as the executing entity of this method; however, in actual implementation, the executing entity of this method can be other names.

[0063] The status information acquisition method includes: acquiring channel data from the first detection device, sending the channel data from the first detection device to the control device, and receiving status information from the control device. The channel data from the first detection device is used to indicate the channel characteristics of the first detection device within a first time period, and the status information is used to indicate whether the channel status of the first detection device is abnormal.

[0064] In the above scheme, channel data is added to the uplink interface between the first detection device and the control device to facilitate the evaluation of the channel status of the first detection device based on the channel data. Status information is added to the downlink interface between the control device and the first detection device to facilitate the calibration of the channel of the first detection device.

[0065] In one possible implementation of the fourth aspect, the channel data of the first detection device includes characteristic data corresponding to the target point collected by the first detection device through the channel during a first time period, and the characteristic data includes amplitude and / or phase.

[0066] In another possible implementation of the fourth aspect, the status information includes anomaly alarm information and / or calibration parameters. The anomaly alarm information indicates an anomaly in the channel status of the first detection device, and the calibration parameters indicate an anomaly in the channel status of the first detection device and are used to calibrate the channel of the first detection device.

[0067] In another possible implementation of the fourth aspect, acquiring channel data of the first detection device includes:

[0068] The initial channel data of the first detection device is acquired, and based on the initial channel data of the first detection device, the channel data of the first detection device is determined. The initial channel data includes characteristic data corresponding to the initial point collected by the first detection device through the channel within a first time period, and the target point is the initial point among the initial points that satisfies a preset second condition.

[0069] In the above embodiments, after the first detection device acquires the initial channel data, it can perform filtering to obtain the target point from the initial point, thereby reducing the amount of channel data of the first detection device, reducing the subsequent data processing time, and improving the efficiency of judging whether the channel status of the detection device is abnormal.

[0070] In another possible implementation of the fourth aspect, the second condition includes at least one of the following: the signal-to-noise ratio corresponding to the point cloud falls within a first range, the first detection device has no abnormal reporting flag, the azimuth angle corresponding to the point cloud falls within a first angular range, the pitch angle corresponding to the point cloud falls within a second angular range, the target object in the point cloud is located within a second distance range, and the point cloud includes multiple initial points.

[0071] Fifthly, this application provides a processing apparatus, which includes a transceiver unit and a processing unit. The transceiver unit is used to acquire channel data of a first detection device, and the processing unit is used to determine the status information of the first detection device based on the channel data. The transceiver unit is also used to transmit status information. The channel data of the first detection device is used to indicate the channel characteristics of the first detection device within a first time period, and the status information is used to indicate whether the channel status of the first detection device is abnormal.

[0072] In one possible implementation of the fifth aspect, the channel data of the first detection device includes characteristic data corresponding to the target point collected by the first detection device through the channel during a first time period, and the characteristic data includes amplitude and / or phase.

[0073] In another possible implementation of the fifth aspect, the transceiver unit is also used to acquire channel data from the first detection device of the first control device.

[0074] In another possible implementation of the fifth aspect, the transceiver unit is also used to send status information to the first control device.

[0075] In another possible implementation of the fifth aspect, the status information includes anomaly alarm information and / or calibration parameters. The anomaly alarm information indicates an anomaly in the channel status of the first detection device, and the calibration parameters indicate the anomaly in the channel status of the first detection device and are used to calibrate the channel of the first detection device.

[0076] In another possible implementation of the fifth aspect, the processing unit is further configured to determine the status information of the first detection device based on the channel data of the first detection device and the channel data of at least two second detection devices. The channel data of the at least two second detection devices are used to indicate the channel characteristics of the at least two second detection devices within a first time period, and the at least two second detection devices are of the same model as the first detection device.

[0077] In another possible implementation of the fifth aspect, the transceiver unit is further configured to acquire channel data from the third detection device of the second control device. The channel data of the third detection device is used to indicate the channel characteristics of the third detection device during a second time period, which includes the first time period, and the third detection device belongs to at least two second detection devices.

[0078] In another possible implementation of the fifth aspect, the processing unit is further configured to determine the state information of the first detection device based on the changes in the channel characteristics of the first detection device during the first time period and the changes in the channel characteristics of at least two second detection devices during the first time period.

[0079] In another possible implementation of the fifth aspect, when the deviation between the change in the channel characteristics of the first detection device during the first time period and the change in the channel characteristics of at least two second detection devices during the first time period satisfies a predefined abnormality condition, the status information is used to indicate an abnormal channel status of the first detection device.

[0080] In another possible implementation of the fifth aspect, the abnormal conditions include abrupt abnormal conditions and non-abrupt abnormal conditions, wherein the abrupt abnormal conditions indicate that the change in the channel characteristics of the first detection device during the first time period deviates abruptly from the change in the channel characteristics of at least two second detection devices during the first time period.

[0081] In another possible implementation of the fifth aspect, the anomalous mutation condition includes: the difference between the maximum deviation data and the minimum deviation data is greater than a second threshold. Here, the maximum deviation data is the maximum value of the difference between the channel data of the first detection device and the channel data of at least two second detection devices within the second sub-time period, and the minimum deviation data is the minimum value of the difference between the channel data of the first detection device and the channel data of at least two second detection devices within the second sub-time period, wherein the second sub-time period belongs to the first time period.

[0082] In another possible implementation of the fifth aspect, the non-mutation anomaly condition includes a gradual anomaly condition and a sustained deviation condition. The gradual anomaly condition indicates that the change in the channel characteristics of the first detection device within a first time period gradually deviates from the changes in the channel characteristics of at least two second detection devices within the same first time period. The sustained deviation condition indicates that the change in the channel characteristics of the first detection device within the first time period continuously deviates from the changes in the channel characteristics of at least two second detection devices within the same first time period.

[0083] In another possible implementation of the fifth aspect, the gradual anomaly condition includes: the difference between the maximum deviation data and the minimum deviation data is greater than a first threshold and less than a second threshold. The maximum deviation data and the minimum deviation data are as described above.

[0084] In another possible implementation of the fifth aspect, the persistent deviation condition includes: the difference between the maximum deviation data and the minimum deviation data is less than a first threshold. The maximum and minimum deviation data are as described above.

[0085] In another possible implementation of the fifth aspect, when the change in the channel characteristics of the first detection device during a first sub-time period deviates from the change in the channel characteristics of the first detection device during other sub-time periods, the status information is used to indicate an abnormal channel status of the first detection device. Here, the first time period includes multiple sub-time periods, the first sub-time period belongs to multiple sub-time periods, and the other sub-time periods are at least two sub-time periods other than the first sub-time period.

[0086] Sixthly, this application provides another processing apparatus, comprising a transceiver unit and a processing unit. The transceiver unit is used to acquire channel data of the detection devices belonging to a first product batch, and the processing unit is used to determine status information based on the channel data of the detection devices belonging to the first product batch. The transceiver unit is also used to transmit the status information. The channel data of the detection devices belonging to the first product batch is used to indicate the channel characteristics of the detection devices belonging to the first product batch within a first time period, and the status information is used to indicate whether the channel status of the detection devices belonging to the first product batch is abnormal.

[0087] In one possible implementation of the sixth aspect, the channel data of the detection device belonging to the first product batch includes characteristic data corresponding to the target point collected by the detection device belonging to the first product batch through the channel in the first time period, and the characteristic data includes amplitude and / or phase.

[0088] In one possible implementation of the sixth aspect, the processing unit is further configured to determine status information based on channel data of the detection devices belonging to the first product batch and channel data of the detection devices belonging to the second product batch. The channel data of the detection devices belonging to the second product batch is used to indicate the channel characteristics of the detection devices belonging to the second product batch during a first time period. The detection devices belonging to the second product batch are of the same model as the detection devices belonging to the first product batch, but from different batches. Optionally, the channel data of the detection devices belonging to the second product batch includes characteristic data corresponding to the target point collected by the detection devices belonging to the second product batch through the channel during the first time period, and the characteristic data includes amplitude and / or phase.

[0089] In one possible implementation of the sixth aspect, the processing unit is further configured to determine status information based on the changes in channel characteristics of the detection device belonging to the first product batch during the first time period and the changes in channel characteristics of the detection device belonging to the second product batch during the first time period.

[0090] In one possible implementation of the sixth aspect, when the channel characteristics of the detection device belonging to the first product batch deviate from the channel characteristics of the detection device belonging to the second product batch within the first time period, the status information is used to indicate that the channel status of the detection device belonging to the first product batch is abnormal.

[0091] In a seventh aspect, this application provides another processing apparatus, which includes a transceiver unit. The transceiver unit is used to acquire channel data of a first detection device, send the channel data of the first detection device to a server, receive status information from the server, and send status information to the first detection device. The channel data of the first detection device is used to indicate the channel characteristics of the first detection device within a first time period, and the status information is used to indicate whether the channel status of the first detection device is abnormal.

[0092] In one possible implementation of the seventh aspect, the channel data of the first detection device includes characteristic data corresponding to the target point collected by the first detection device through the channel during a first time period, and the characteristic data includes amplitude and / or phase.

[0093] In another possible implementation of the seventh aspect, the status information includes anomaly alarm information and / or calibration parameters. The anomaly alarm information is used to indicate an anomaly in the channel status of the first detection device, and the calibration parameters are used to indicate an anomaly in the channel status of the first detection device and to calibrate the channel of the first detection device.

[0094] In another possible implementation of the seventh aspect, the transceiver unit is further configured to receive channel data of the first detection device reported by the first detection device.

[0095] In another possible implementation of the seventh aspect, the transceiver unit is further configured to receive candidate channel data of the first detection device reported by the first detection device. The processing device further includes a processing unit configured to determine channel data of the first detection device based on the candidate channel data of the first detection device. The candidate channel data includes characteristic data corresponding to candidate points collected by the first detection device through the channel within a first time period, and the target point is a candidate point among the candidate points that meets a preset first condition.

[0096] In yet another possible implementation of the seventh aspect, the first condition includes at least one of the following:

[0097] The number of target objects in the point cloud meets preset quantity conditions and / or preset distance conditions, and the acquisition scene when the point cloud is acquired meets preset scene conditions. The preset distance condition is used to constrain the distance between the target objects and the first detection device. The point cloud includes multiple candidate points.

[0098] In another possible implementation of the seventh aspect, the number of target objects in the point cloud satisfies a preset quantity condition and / or a preset distance condition, including: the target objects in the point cloud are isolated target objects and the isolated target objects are located within a first distance range.

[0099] Eighthly, this application provides another processing apparatus, which includes a transceiver unit for acquiring channel data of a first detection device, sending the channel data of the first detection device to the processing apparatus, and receiving status information from the processing apparatus. The channel data of the first detection device is used to indicate the channel characteristics of the first detection device within a first time period, and the status information is used to indicate whether the channel status of the first detection device is abnormal.

[0100] In one possible implementation of the eighth aspect, the channel data of the first detection device includes characteristic data corresponding to the target point collected by the first detection device through the channel during a first time period, and the characteristic data includes amplitude and / or phase.

[0101] In another possible implementation of the eighth aspect, the status information includes anomaly alarm information and / or calibration parameters. The anomaly alarm information indicates an anomaly in the channel status of the first detection device, and the calibration parameters indicate the anomaly in the channel status of the first detection device and are used to calibrate the channel of the first detection device.

[0102] In another possible implementation of the eighth aspect, the transceiver unit is used to acquire initial channel data of the first detection device. The processing device further includes a processing unit, which is used to determine channel data of the first detection device based on the initial channel data of the first detection device. The initial channel data includes characteristic data corresponding to initial points collected by the first detection device through the channel within a first time period, and the target point is an initial point among the initial points that satisfies a preset second condition.

[0103] In another possible implementation of the eighth aspect, the second condition includes at least one of the following: the signal-to-noise ratio corresponding to the point cloud falls within a first range, the first detection device has no abnormal reporting flag, the azimuth angle corresponding to the point cloud falls within a first angular range, the pitch angle corresponding to the point cloud falls within a second angular range, the target object in the point cloud is located within a second distance range, and the point cloud includes multiple initial points.

[0104] Ninthly, embodiments of this application provide a server connected to a control device. The server includes a processor and a memory, the memory storing a program, and the processor executing the program stored in the memory to enable the server to implement the method described in either the first or second aspect.

[0105] In a tenth aspect, embodiments of this application provide a detection device connected to a control device. The detection device includes a processor and a memory, the memory storing a program, and the processor executing the program stored in the memory to enable the detection device to implement the method described in any of the preceding fourth aspects.

[0106] Eleventhly, embodiments of this application provide a control device connected to a server and a detection device. The detection device includes a processor and a memory, the memory storing a program, and the processor executing the program stored in the memory to enable the detection device to implement the method described in any of the preceding third aspects.

[0107] In a twelfth aspect, embodiments of this application provide a computer-readable storage medium for storing a computer program, the computer program including instructions for performing the methods described in any one of the first, second, third, or fourth aspects.

[0108] In a thirteenth aspect, this application provides a computer program product including computer instructions that, when executed by a processor, cause the methods described in any one of the first, second, third, or fourth aspects to be implemented.

[0109] The solutions provided in the fifth, sixth, ninth, twelfth and thirteenth aspects above are used to implement or cooperate with the methods provided in the first and second aspects above, and therefore can achieve the same or corresponding beneficial effects as the first and second aspects, which will not be elaborated here.

[0110] The solutions provided in aspects 7, 11, 12 and 13 above are used to implement or cooperate with the methods provided in aspect 3 above, and therefore can achieve the same or corresponding beneficial effects as aspect 3, which will not be elaborated here.

[0111] The solutions provided in aspects eight, ten, twelfth and thirteen above are used to implement or cooperate with the methods provided in aspect four above, and therefore can achieve the same or corresponding beneficial effects as aspect four, which will not be elaborated here. Attached Figure Description

[0112] The accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0113] Figure 1a is a schematic diagram of the architecture of a management system provided in an embodiment of this application;

[0114] Figure 1b is a schematic diagram of the architecture of another management system provided in an embodiment of this application;

[0115] Figure 2a is a schematic diagram of the architecture of another management system provided in an embodiment of this application;

[0116] Figure 2b is a schematic diagram of the architecture of another management system provided in an embodiment of this application;

[0117] Figure 3 is a flowchart illustrating a method for obtaining status information provided in an embodiment of this application;

[0118] Figure 4 is a schematic diagram of characteristic data provided in an embodiment of this application;

[0119] Figure 5 is a schematic diagram of a characteristic data mutation anomaly provided in an embodiment of this application;

[0120] Figure 6 is a schematic diagram of a characteristic data gradient anomaly provided in an embodiment of this application;

[0121] Figure 7 is a schematic diagram of a continuous deviation of characteristic data provided in an embodiment of this application;

[0122] Figure 8 is a flowchart illustrating another method for obtaining status information provided in an embodiment of this application;

[0123] Figure 9 is a flowchart illustrating another method for obtaining status information provided in an embodiment of this application;

[0124] Figure 10 is a schematic diagram of characteristic data of a detection device for different product batches provided in an embodiment of this application;

[0125] Figure 11 is a schematic diagram of a processing device provided in an embodiment of this application;

[0126] Figure 12 is a schematic diagram of another processing device provided in an embodiment of this application;

[0127] Figure 13 is a schematic diagram of another processing device provided in an embodiment of this application;

[0128] Figure 14 is a schematic diagram of another processing device provided in an embodiment of this application;

[0129] Figure 15 is a schematic diagram of the structure of a server provided in an embodiment of this application;

[0130] Figure 16 is a schematic diagram of a control device provided in an embodiment of this application;

[0131] Figure 17 is a schematic diagram of the structure of a detection device provided in an embodiment of this application. Detailed Implementation

[0132] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0133] For ease of understanding, the following examples illustrate some concepts related to the embodiments of this application for reference. As follows:

[0134] 1. Detection device

[0135] The detection device is capable of emitting signals to detect targets. The detection device includes, but is not limited to, radar or lidar. The radar can be millimeter-wave radar, centimeter-wave radar, etc. In some scenarios, a device that integrates both radar (or lidar) and a camera (a fusion detection device) can also detect targets; this fusion detection device also falls within the scope of the detection device described in this application.

[0136] 2. Channel

[0137] Radar systems typically include multiple channels, each responsible for receiving and processing signals from different directions or frequencies. These channels can be physically independent antennas or frequency bands, or different processing units in signal processing. Channel status includes whether the channel is operating normally, signal strength, noise level, etc. In the embodiments of this application, a channel can be understood as an independent antenna of the detection device.

[0138] As the shipment volume of detection devices increases and the operating time in the network grows, the impact of channel status anomalies caused by factors such as device contamination, deformation, and aging is gradually becoming apparent. These anomalies typically exhibit time-varying characteristics, cannot be compensated for using the initial equipment list obtained before the detection device leaves the factory, and are not detected by routine hardware self-tests. When this impact reaches a certain level, it can lead to a significant decrease in the angle measurement capability of the detection device, causing anomalies in the reported point cloud and affecting the detection capability of the device.

[0139] 3. Closest in-path vehicle (CIPV)

[0140] CIPV (Compatible Vehicle Location) refers to the nearest vehicle on the path of an autonomous vehicle. Identifying and monitoring CIPVs is crucial for improving driving performance and safety in autonomous driving systems. By identifying CIPVs, autonomous vehicles can better predict the trajectories of other vehicles, thereby making more informed driving decisions and avoiding potential collision risks.

[0141] 4. Product batch

[0142] In this application embodiment, a product batch can be a collection of products produced during the production process according to the same time period, the same process conditions, and the same raw materials. For example, products of the same model produced within the same time period using the same production line and the same process are referred to as a product batch. For instance, 500 detectors of the same model produced by a detection device manufacturing plant from month 1 to month 15 using the same raw materials, the same production line, and the same process constitute a product batch. This application does not limit the specific definition of a product batch; the definition is for reference by those skilled in the art to achieve status information acquisition.

[0143] The above descriptions of technical terms may be used in the embodiments below.

[0144] The management system described below is an introduction to this application. It should be noted that the system architecture and business scenarios described in this application are for the purpose of more clearly illustrating the technical solution of this application and do not constitute a limitation on the technical solution provided in this application. As system architecture evolves and new business scenarios emerge, the technical solution provided in this application is equally applicable to similar technical problems.

[0145] Please refer to Figure 1a, which is a schematic diagram of the architecture of a management system provided in an embodiment of this application. The management system 10 includes a detection device 101 and a processing device 102. The various modules in the management system 10 are described below:

[0146] The detection device 101 has detection capabilities. For example, the detection device 101 can emit a detection signal towards a target and receive the echo returned by the target to obtain a point cloud. The channel data corresponding to this point cloud can be used to evaluate the channel status of the detection device 101. The channel data is used to indicate the channel characteristics of the detection device 101. For example, the channel data includes characteristic data corresponding to the target point collected by the detection device through the channel in a first time period, and the characteristic data includes amplitude and / or phase. The target point belongs to the point cloud. Optionally, the detection device 101 can be a lidar, millimeter-wave radar, centimeter-wave radar, or a fusion detection device, etc.

[0147] The processing device 102 has data processing and communication capabilities. The processing device 102 is connected to the detection device 101, and can receive (or output) channel data from the detection device 101 via the connection line between them. Further, the processing device 102 can determine the status information of the detection device 101 based on the channel data. This status information indicates whether the channel status of the detection device 101 is abnormal. Optionally, the processing device 102 can send (or output) status information to the detection device 101 via the connection line between them.

[0148] As one possible implementation, the processing device 102 can be a physical device, such as including one or more of the following modules: central processing unit (CPU), microprocessor unit (MPU), application specific-integrated circuit (ASIC), field programmable gate array (FPGA), complex programmable logic device (CPLD), coprocessor (assisting the central processing unit in completing corresponding processing and applications), microcontroller unit (MCU), domain controller, and / or electronic control unit (ECU), etc.

[0149] Of course, Figure 1a above describes the case where the processing device 102 is located inside the vehicle. In some solutions, the processing device 102 can be a physical device located outside the vehicle, such as a server, cloud, or host. As one possible implementation, the processing device 102 can be a software module, such as a virtual machine, software, program code, or container. Referring to Figure 1b, the processing device 102 is located outside the vehicle. In this case, the management system 10 also includes a control device 103 located inside the vehicle. The control device 103 has data processing and communication capabilities. Exemplarily, the processing device 102 is connected to the control device 103, and the control device 103 is connected to the detection device 101, thereby enabling communication between the processing device 102 and the detection device 101. For example, the control device 103 can receive channel data from the detection device 101 and send the channel data of the detection device 101 to the processing device 102, so that the processing device 102 can obtain the channel data of the detection device 101. For example, the control device 103 can receive status information from the processing device 102 and send status information to the detection device 101 so that the detection device 101 can acquire the status information. Optionally, the control device 103 may include one or more of the following modules: CPU, MPU, ASIC, FPGA, CPLD, coprocessor (to assist the central processing unit in completing corresponding processing and applications), MCU, domain controller, and / or ECU, etc.

[0150] In one possible implementation, as shown in FIG1a, the detection device 101 sends the channel data of the detection device 101 to the processing device 102. Further, the processing device 102 determines the status information of the detection device 101 based on the channel data of the detection device 101, and sends the status information to the detection device 101.

[0151] In another possible implementation, as shown in Figure 1b, the detection device 101 sends its channel data to the control device 103, and the control device 103 sends the channel data of the detection device 101 to the processing device 102. Further, the processing device 102 determines the status information of the detection device 101 based on the channel data and sends the status information to the control device 103. After receiving the status information, the control device 103 can send status information back to the detection device 101. The channel data is used to indicate the channel characteristics of the detection device 101 within a first time period.

[0152] In this application, the processing device can sense and evaluate anomalies in the channel status of the detection device based on channel data from the detection device within a certain time period, effectively monitoring the channels of the detection device. Furthermore, the processing device can identify anomalies in the channel status of the detection device throughout its lifecycle, helping to promptly detect abnormal channel states and ensuring the reliability of the detection device's sensing capabilities. For example, if the first time period is from the time the first detection device was manufactured to the current time, the processing device can monitor the channel status throughout the entire lifecycle of the detection device, improving its reliability.

[0153] Especially in scenarios where the detection device is installed in a vehicle, the detection results are typically used for the vehicle's intelligent functions, such as intelligent driving systems, autonomous driving systems, and automatic parking systems. Using the solution of this application, if the detection device is installed in a vehicle, this application can also ensure the reliability of the vehicle's intelligent functions and improve the safety of passengers.

[0154] Please refer to Figure 2a, which is a schematic diagram of the architecture of another management system provided in an embodiment of this application. The management system 20 includes multiple detection devices (e.g., detection device 101a, detection device 101b, detection device 101n, etc.), a processing device 102, and a management device 104. The various modules in the management system 20 are described below:

[0155] Detection devices 101a, 101b, 101n, etc., can be found in the description of detection device 101 above. Each of the multiple detection devices in the management system 20 has the same model number and belongs to at least one product batch, including a first product batch. For example, among the multiple detection devices, there are n detection devices, x of which belong to the first product batch (e.g., detection devices 101a to 101x), and y of which belong to the second product batch (e.g., detection devices 101y to 101n). Here, n, x, and y are all integers, and n, x, and y are all greater than 0, and the sum of x and y is less than or equal to n.

[0156] The processing device 102 is described above. The processing device 102 can receive channel data from multiple detection devices to obtain channel data belonging to the first product batch, and based on the channel data of the detection devices belonging to the first product batch, determine status information indicating whether the channel status of the detection devices belonging to the first product batch is abnormal. Optionally, the processing device 102 can send the status information to the management device 104.

[0157] Figure 2a above describes an example where the processing device 102 is located inside a vehicle. In some embodiments, the processing device 102 can be a physical device located outside the vehicle, such as a server, cloud, or host. As one possible implementation, the processing device 102 can be a software module, such as a virtual machine, software, program code, or container. Referring to Figure 2b, the processing device 102 is located outside the vehicle. In this case, the management system 20 also includes multiple control devices (e.g., control device 103a, control device 103b, control device 103n, etc.). Figure 2b illustrates an example where one detection device is connected to one control device and is located in the same vehicle. Of course, in actual use, the control device can be connected to a larger number of detection devices. The control device can be referred to in the previous description of control device 103. Exemplarily, the processing device 102 is connected to the control device 103a, and the control device 103a is connected to the detection device 101a, thereby enabling communication between the processing device 102 and the detection device 101a. For example, control device 103a can receive channel data from detection device 101a and send the channel data of detection device 101a to processing device 102, so that processing device 102 can acquire the channel data of detection device 101a. Similarly, communication between processing device 102 and detection device 101b is achieved through control device 103b, and communication between processing device 102 and detection device 101n is achieved through control device 103n. In this way, processing device 102 can receive channel data from multiple detection devices through multiple control devices, thereby acquiring the channel data of the detection devices belonging to the first product batch.

[0158] The management device 104 is a communication-capable device. Optionally, the management device 104 may be a device used by a manufacturer of multiple detection devices (e.g., detection device 101a, detection device 101b, detection device 101n, etc.). Exemplarily, the management device 104 can receive information from the processing device 102. For example, the management device 104 can receive status information from the processing device 102. Optionally, the management device 104 can interact with a user, such as presenting a user interface or receiving user input. For example, the management device 104 can display status information to the user. Exemplarily, the management device 104 includes, but is not limited to, handheld terminals, wearable devices, entertainment devices, transportation devices, etc. Handheld devices include, for example, mobile phones, tablets, laptops, or police communication devices. Wearable devices include, for example, smart bracelets, smartwatches, or smart glasses.

[0159] In one possible implementation, as shown in Figure 2a, multiple detection devices (e.g., detection device 101a, detection device 101b, detection device 101n, etc.) send channel data of multiple detection devices to processing device 102. Processing device 102 obtains the channel data of the detection devices belonging to the first product batch among the multiple detection devices, and determines status information based on the channel data of the detection devices belonging to the first product batch. Optionally, processing device 102 sends status information to management device 104.

[0160] In another possible implementation, as shown in Figure 2b, each of the multiple detection devices (e.g., detection devices 101a, 101b, 101n, etc.) sends its channel data to a control device (e.g., control device 103a, 103b, 103n, etc.) connected to the multiple detection devices respectively. The multiple control devices (e.g., control device 103a, 103b, 103n, etc.) send the channel data of the multiple detection devices to the processing device 102. The processing device 102 obtains the channel data of the detection devices belonging to a first product batch and determines status information based on the channel data of the detection devices belonging to the first product batch. Optionally, the processing device sends the status information to the management device 104. Here, the multiple detection devices belong to at least one product batch, and the at least one product batch includes the first product batch; the status information is used to indicate whether the channel status of the detection devices belonging to the first product batch is abnormal.

[0161] In this application, the processing device can determine whether the channel status of a certain batch of detection devices is abnormal based on the channel data of multiple detection devices, which can effectively monitor the channels of the entire batch of detection devices and help to provide early warning of potential network problems.

[0162] The method for obtaining status information provided in this application is described below.

[0163] Please refer to Figure 3, which is a flowchart illustrating a status information acquisition method provided in an embodiment of this application. Optionally, this status information acquisition method can be applied to the management system 10 shown in Figure 1a or Figure 1b. The method shown in Figure 3 includes at least the following steps:

[0164] Step S301: The processing device acquires the channel data of the first detection device.

[0165] The detection device has detection capabilities, such as the detection device 101 shown in Figure 1a or Figure 1b. Optionally, the detection device can be a lidar, millimeter-wave radar, centimeter-wave radar, or a fusion detection device, etc. For ease of description, the first detection device will be described below.

[0166] The processing device has data processing and communication capabilities, such as the processing device 102 shown in Figure 1a or Figure 1b. Optionally, the processing device may be a domain controller, server, etc.

[0167] For example, the processing device is connected to the first detection device, which can acquire channel data and send the channel data to the processing device. Correspondingly, the processing device receives the channel data from the first detection device.

[0168] For example, the first detection device can emit a detection signal towards the target object and receive the echo returned by the target object to obtain a point cloud. The channel data corresponding to this point cloud can be used to evaluate the channel status of the first detection device. The channel data indicates the channel characteristics of the first detection device within a first time period. The first time period is a predefined or set time period, for example, the first time period could be the time period between the device's manufacturing date and the current date. In one possible implementation, the channel data includes characteristic data corresponding to the target point collected by the first detection device through the channel within the first time period, and the characteristic data includes amplitude and / or phase. The target point belongs to the point cloud. For example, the channel data includes characteristic data corresponding to the target point collected by the first detection device through the channel within the time period between the device's manufacturing date and the current date.

[0169] In one possible implementation, the channel data corresponding to each point in the point cloud is used to indicate the channel characteristics of the first detection device. The channel data of the first detection device includes the characteristic data corresponding to each point in the point cloud obtained by the first detection device, that is, the amplitude and / or phase corresponding to each point. In this case, the target point includes all points in the point cloud.

[0170] As another possible implementation, the target point is a point in the point cloud that satisfies a preset second condition. For example, the first detection device acquires initial channel data, which includes characteristic data corresponding to initial points (i.e., all points in the point cloud, which can be referred to as initial points for ease of description) collected by the first detection device through channels within a first time period. Further, the first detection device determines its own channel data based on the initial channel data. In this case, the target point is a point among the initial points that satisfies the preset second condition.

[0171] The second condition includes at least one of the following: the signal-to-noise ratio (SNR) of the point cloud falls within a first range; the first detection device reports no abnormality; the azimuth angle of the point cloud falls within a first angle range; the pitch angle of the point cloud falls within a second angle range; and the target object in the point cloud is located within a second distance range. The point cloud includes multiple initial points, or all points in the point cloud are initial points. For example, the first range is a pre-set SNR range; if the SNR of a point falls within this range, it indicates that the phase of that point is relatively stable. For example, the first range could be 20dB to 30dB. The absence of an abnormality reporting flag from the first detection device indicates that the acquisition scene corresponding to the point is an interference-free scene, the occlusion or calibration is normal, and there is no saturation alarm. The first angle range is a pre-set angle range; if the azimuth angle of a point falls within this angle range, it indicates that the radiation pattern of that point is stable, the amplitude and phase inconsistencies have a small impact, and the characteristic data corresponding to that point can be used for comparison. For example, the first angle range could be -3° to 3°. The second angle range is a pre-set angle range. If the pitch angle corresponding to a point falls within this range, it indicates that the radiation pattern of that point is stable, and the impact of amplitude and phase inconsistencies is minimal. The characteristic data corresponding to that point can be used for comparison. For example, it could be -3° to 3°. The second distance range is used to constrain the distance between the target object and the first detection device. If the distance between the target object in the point cloud and the first detection device falls within this distance range, it indicates that the multipath or multihop influence of that point is minimal, and it is located at a single scattering center. For example, the second distance range could be 100 meters to 200 meters.

[0172] In one possible implementation, the processing device receives the channel data of the first detection device reported by the first detection device without processing the channel data reported by the first detection device. In this case, the channel data of the first detection device reported by the first detection device is the same as the channel data of the first detection device acquired by the processing device.

[0173] In another possible implementation, the processing device receives channel data (which may be referred to as candidate channel data) reported by the first detection device, and determines the channel data of the first detection device based on the candidate channel data. The candidate channel data includes characteristic data corresponding to candidate points collected by the first detection device through the channel within a first time period, and the target point is a candidate point among the candidate points that meets a preset first condition. In other words, after receiving the candidate channel data reported by the first detection device, the processing device can perform filtering to obtain the target point from the candidate points, thereby obtaining the characteristic data corresponding to the target point collected by the first detection device through the channel within the first time period.

[0174] For example, the first condition includes the number of target objects in the point cloud meeting a preset quantity condition and / or a preset distance condition. And / or, the first condition includes the acquisition scene when the point cloud is acquired meeting a preset scene condition.

[0175] The point cloud includes multiple candidate points, or all points in the point cloud are candidate points. The number of target objects in the point cloud meets preset quantity conditions and / or preset distance conditions, including that the target objects in the point cloud are isolated target objects and that the isolated target objects are located within a first distance range. For example, the target object in the point cloud is located within the first distance range and that target object is an isolated CIPV target. The preset distance conditions are used to constrain the distance between the target object and the first detection device, for example, the first distance range can be 100 meters to 200 meters. Preset scene conditions include sparse curb points, no curb when the distance to the first detection device is greater than a distance threshold, isolated road signs, isolated gantry structures, etc.

[0176] Alternatively, this implementation method can be combined with the implementation methods described above. For example, all points in the point cloud are the initial points described above, the points among the initial points that meet the preset second condition are candidate points, and the points among the candidate points that meet the preset first condition are target points. That is, the target points are obtained after the point cloud is filtered twice.

[0177] The first and second conditions mentioned above are merely illustrative examples. In actual use, there may be many more possible designs, which will not be listed here.

[0178] Step S302: The processing device determines the status information of the first detection device based on the channel data of the first detection device.

[0179] The status information includes abnormal alarm information and / or calibration parameters. The abnormal alarm information indicates an abnormal channel status of the first detection device, for example, an abnormal alarm message stating "The channel status of the first detection device is abnormal." The calibration parameters indicate the abnormal channel status of the first detection device and are used to calibrate the channel of the first detection device. For example, the calibration parameters can reduce the deviation between the channel data of the first detection device and normal data to fall within a first value range. For example, the first value range is a pre-set acceptable range; for example, the acceptable range for phase data can be -0.5 degrees to +0.5 degrees. The above implementation can reduce the impact of abnormal channel characteristics on the detection capability of the detection device, improve the detection accuracy of the detection device, and ensure the reliability of the detection device's sensing.

[0180] Optionally, the processing device may determine the status information of the first detection device based solely on the channel data of the first detection device, without using the channel data of other detection devices. Alternatively, the processing device may jointly determine the status information of the first detection device based on the channel data of the first detection device and the channel data of other detection devices. These two implementation methods are described below.

[0181] In the first implementation method, the processing device determines the status information of the first detection device based solely on the channel data of the first detection device.

[0182] For example, the first time period includes multiple sub-time periods. When the change in the channel characteristics of the first detection device within the first sub-time period deviates from the change in the channel characteristics of the first detection device within other sub-time periods, the status information is used to indicate an abnormal channel status of the first detection device. The change in channel characteristics can be reflected through changes in characteristic data. The first sub-time period belongs to multiple sub-time periods, and the other sub-time periods are at least two sub-time periods other than the first sub-time period. The length of each sub-time period can be the same. Referring to Figure 4, if the characteristic data of the first detection device suddenly increases within the first sub-time period, while the characteristic data of the first detection device fluctuates less within other sub-time periods, it is clear that the change in the channel characteristics of the first detection device within the first sub-time period deviates from the change in the channel characteristics of the first detection device within other sub-time periods. At this time, the channel status of the first detection device is very likely to be abnormal, and the status information of the first detection device determined by the processing device is used to indicate an abnormal channel status of the first detection device. The calibration parameters can reduce the difference between the characteristic data acquired by the first detection device after calibration and the characteristic data acquired by the first detection device within other sub-time periods to fall within a first value range.

[0183] In the second implementation method, the processing device determines the status information of the first detection device based on the channel data of the first detection device and the channel data of other detection devices.

[0184] For example, the processing device determines the status information of the first detection device based on the channel data of the first detection device and the channel data of at least two second detection devices. The at least two second detection devices are of the same model as the first detection device, and the channel data of the at least two second detection devices are used to indicate the channel characteristics of the at least two second detection devices within a first time period. Optionally, the at least two second detection devices belong to the same product batch as the first detection device. Similarly, the channel data of the at least two second detection devices includes characteristic data corresponding to the target point collected by the at least two second detection devices through the channel within the first time period, and the characteristic data includes amplitude and / or phase.

[0185] Optionally, the channel data of at least two second detection devices can also be obtained by each of the at least two second detection devices and then reported to the processing device.

[0186] Similarly, each of the at least two second detection devices can filter points in the point cloud, and the processing device can also filter points in the point cloud. For details on the filtering operation, please refer to the relevant description above.

[0187] In one possible implementation, the processing device can determine the status information of the first detection device based on the changes in the channel characteristics of the first detection device during a first time period and the changes in the channel characteristics of at least two second detection devices during the same time period. Optionally, the processing device can obtain the changes in the channel characteristics of the first detection device during the first time period based on the channel data of the first detection device, and obtain the changes in the channel characteristics of at least two second detection devices during the same time period based on the channel data of the at least two second detection devices. Further, the processing device determines the status information of the first detection device based on the changes in the channel characteristics of the first detection device during the first time period and the changes in the channel characteristics of the at least two second detection devices during the same time period. For example, when the deviation between the changes in the channel characteristics of the first detection device during the first time period and the changes in the channel characteristics of the at least two second detection devices during the same time period satisfies a predefined abnormality condition, the status information is used to indicate an abnormal channel status of the first detection device.

[0188] The abnormal conditions include abrupt change abnormal conditions and non-abrupt change abnormal conditions. Abrupt change abnormal conditions indicate a sudden deviation in the channel characteristics of the first detection device within a first time period relative to the channel characteristics of at least two second detection devices within the same first time period. For example, abrupt change abnormal conditions include a difference between the maximum and minimum deviation data exceeding a second threshold. The maximum deviation data is the maximum difference between the characteristic data of the first detection device and the characteristic data of at least two second detection devices within a second sub-time period, and the minimum deviation data is the minimum difference between the characteristic data of the first detection device and the characteristic data of at least two second detection devices within the second sub-time period. The second sub-time period belongs to the first time period. Referring to Figure 5, taking two second detection devices as an example, R1 is the first detection device, and R2 and R3 are the two second detection devices. The deviation data is the difference between the characteristic data of R1 and the characteristic data of R2 and R3 within the first time period. 'a' represents the maximum deviation data of R1 within the second sub-time period, and 'b' represents the minimum deviation data of R1 within the second sub-time period. When the difference between a and b is greater than the second threshold, the deviation between the changes in channel characteristics of R1 and R2 and R3 in the first time period is determined to meet the abrupt change anomaly condition. The status information is used to indicate an abnormal channel status of the first detection device. The second threshold is a pre-set or pre-defined difference threshold. When the deviation data of the detection device in the second sub-time period is greater than the second threshold, it can be considered that the detection device suddenly deviates during this time period, and the deviation change is large, constituting an abrupt change anomaly. Since the channel status anomalies caused by external force deformation of the detection device are usually sudden, the above implementation can determine whether the abrupt change anomaly condition is met based on the channel data of the detection device. Therefore, the above implementation can identify channel status anomalies caused by external force deformation of the detection device.

[0189] Non-mutational anomaly conditions include gradual anomaly conditions and continuous deviation conditions. Gradual anomaly conditions indicate that the change in channel characteristics of the first detection device within a first time period gradually deviates from the changes in channel characteristics of at least two second detection devices within the same first time period. For example, a gradual anomaly condition includes a difference between the maximum and minimum deviation data being greater than a first threshold and less than a second threshold. The maximum and minimum deviation data are described in the foregoing related descriptions. Referring to Figure 6, taking two second detection devices as an example, R4 is the first detection device, and R5 and R6 are two second detection devices. The deviation data is the difference between the characteristic data of R4 within the first time period and the characteristic data of R5 and R6 within the first time period. c is the maximum value of the deviation data of R4 within the second sub-time period, and d is the minimum value of the deviation data of R4 within the second sub-time period. When the difference between c and d is greater than the first threshold and less than the second threshold, the deviation between the change in channel characteristics of R4 within the first time period and the changes in channel characteristics of R5 and R6 within the first time period is determined to satisfy the gradual anomaly condition, and the status information is used to indicate an anomaly in the channel status of the first detection device. The second threshold is described above, and the first threshold is a pre-set or pre-defined difference threshold. When the deviation data of the detection device in the second sub-time period is greater than the first threshold and less than the second threshold, it can be considered that the detection device has deviated during this time period, and the deviation change is small, which is a gradual anomaly. Since the channel state anomalies caused by dirt / aging of the detection device are usually slow changes, the above implementation can determine whether the gradual anomaly condition is met based on the channel data of the detection device. Therefore, the above implementation can identify the channel state anomalies caused by dirt / aging of the detection device.

[0190] The sustained deviation condition indicates that the change in channel characteristics of the first detection device during a first time period continuously deviates from the changes in channel characteristics of at least two second detection devices during the same time period. For example, the sustained deviation condition includes a difference between the maximum and minimum deviation data being less than a first threshold. The maximum and minimum deviation data are described in the foregoing related descriptions. Referring to Figure 7, taking two second detection devices as an example, R7 is the first detection device, and R8 and R9 are two second detection devices. The deviation data is the difference between the characteristic data of R7 and the characteristic data of R8 and R9 during the first time period. e is the maximum value of the deviation data of R7 during a second sub-time period, and f is the minimum value of the deviation data of R7 during the second sub-time period. When the difference between e and f is less than the first threshold, it is determined that the deviation between the change in channel characteristics of R7 and the changes in channel characteristics of R8 and R9 during the first time period satisfies the sustained deviation condition, and the status information is used to indicate an abnormal channel status of the first detection device. The first threshold is as described above. When the deviation data of the detection device in the second sub-time period is less than the first threshold, it can be considered that the detection device has deviated during this time period, and the deviation change is very small (e.g., the deviation does not change significantly over time), which is a continuous deviation anomaly. Since the channel state anomaly caused by the large difference between the module operating conditions inside the detection device and the standard operating conditions when the equipment is tabulated (e.g., voltage, temperature, humidity, etc.) is usually stable but continuously deviating, the above implementation can determine whether the continuous deviation condition is met based on the channel data of the detection device. Thus, the above implementation can identify the channel state anomaly caused by the large difference between the module operating conditions inside the detection device and the standard operating conditions when the equipment is tabulated (e.g., voltage, temperature, humidity, etc.).

[0191] The above abnormal conditions are merely illustrative examples. In actual use, there may be many more possible designs, which will not be listed here.

[0192] The above implementation uses two second detection devices as an example. Of course, in actual use, there may be more second detection devices, as long as the number is greater than or equal to 2.

[0193] Optionally, after receiving the status information, the processing device can display alarm information to the user. The alarm information is used to indicate that there is an anomaly in the detection information of the detection device, such as the alarm information being "the channel status of the first detection device is abnormal, and the detection information of the current detection device may be incorrect." Optionally, the processing device can display the alarm information on a screen or play the alarm information through a speaker.

[0194] Furthermore, when the first detection device and the processing device are installed in a vehicle, the processing device can also shield some intelligent functions related to the detection information of the first detection device.

[0195] Optionally, the processing device may send status information. For example, the processing device sends status information to the first detection device. Correspondingly, the first detection device receives status information from the processing device. For example, when the status information includes calibration parameters, the first detection device may operate a self-calibration function; for instance, the first detection device may calibrate its channels based on the calibration parameters, reducing the deviation between the channel data and normal data to fall within a first value range.

[0196] In the embodiment shown in Figure 3, the processing device can acquire channel data from the first detection device and determine whether the channel status of the first detection device is abnormal based on the channel data. The channel data of the first detection device is used to indicate the channel characteristics of the first detection device within a first time period. In this application, the processing device can comprehensively analyze the channel data of the detection device within a certain time period to perceive and evaluate abnormalities in the channel status of the detection device, effectively monitoring the channels of the detection device. Furthermore, the processing device can identify abnormalities in the channel status of the detection device within a certain lifespan, helping to promptly detect abnormal channel states and ensuring the reliability of the detection device's sensing capabilities. For example, if the first time period is the period from the manufacturing date of the first detection device to the current date, the processing device can monitor the channel status throughout the entire lifespan of the detection device, improving the reliability of the detection device.

[0197] Especially in scenarios where the detection device is installed in a vehicle, the detection results are typically used for the vehicle's intelligent functions, such as intelligent driving systems, autonomous driving systems, and automatic parking systems. Utilizing the solution in this application can ensure the reliability of the vehicle's intelligent functions and improve user safety while riding in the vehicle.

[0198] The embodiments shown in Figure 3 above encompass various possible scenarios. The following description, in conjunction with Figure 8, introduces one possible implementation of an embodiment of this application, where a portion of the processing device's functions are executed by the control device, and another portion by the server. In the following description, any terms, logic, etc., not explained herein can be found in the above description.

[0199] Step S801: The first detection device acquires the channel data of the first detection device.

[0200] The detection device has detection capabilities, such as the detection device 101 shown in Figure 1a or Figure 1b. Optionally, the detection device can be a lidar, millimeter-wave radar, centimeter-wave radar, or a fusion detection device, etc. For ease of description, the first detection device will be described below.

[0201] For example, the first detection device can transmit a detection signal to the target and receive the echo returned by the target to obtain a point cloud. The channel data corresponding to the point cloud can be used to evaluate the channel status of the first detection device.

[0202] In one possible implementation, the channel data corresponding to each point in the point cloud is used to indicate the channel characteristics of the first detection device. The channel data of the first detection device includes the characteristic data corresponding to each point in the point cloud obtained by the first detection device, that is, the amplitude and / or phase corresponding to each point. In this case, the target point includes all points in the point cloud.

[0203] As another possible implementation, the target point is a point in the point cloud that satisfies a preset second condition.

[0204] For details on the acquisition and screening process, please refer to the relevant description in step S301 above.

[0205] Step S802: The first detection device sends the channel data of the first detection device to the control device.

[0206] For example, the first detection device sends the channel data of the first detection device to a control device (which may be referred to as the first control device for ease of description) connected to the first detection device.

[0207] Accordingly, the first control device receives channel data from the first detection device. Thus, channel data is added to the uplink interface between the first detection device and the first control device to facilitate subsequent evaluation of the channel status of the detection device based on the channel data.

[0208] The control device has data processing and control capabilities, such as the control device 103 shown in Figure 1b. Optionally, the control device can be a domain controller, MCU, etc.

[0209] In one possible implementation, the first control device receives the channel data of the first detection device reported by the first detection device without processing it. In this case, the channel data of the first detection device reported by the first detection device is the channel data of the first detection device.

[0210] As another possible implementation, the first control device receives the channel data of the first detection device (which may be referred to as alternative channel data for ease of description) reported by the first detection device, and determines the channel data of the first detection device based on the alternative channel data of the first detection device.

[0211] For details on the screening process, please refer to the relevant description in step S301 above.

[0212] Step S803: The control device sends the channel data of the first detection device to the server.

[0213] A server is a device with centralized computing and communication capabilities, such as the processing device 102 shown in Figure 1b.

[0214] For example, a control device connected to the first detection device (i.e., the first control device mentioned above) sends the channel data of the first detection device to the server.

[0215] Accordingly, the server receives channel data from the first detection device of the first control device. Thus, channel data is added to the uplink interface between the first control device and the server to facilitate the evaluation of the channel status of the first detection device based on the channel data.

[0216] Optionally, the operation of the first control device to filter and obtain the target point described above can also be performed by the server. For example, the first control device receives the channel data (which may be referred to as alternative channel data for ease of description) reported by the first detection device and directly sends the alternative channel data of the first detection device to the server. The server receives the alternative channel data of the first detection device and determines the channel data of the first detection device based on the alternative channel data. The alternative channel data and the filtering process can be found in the relevant description in step S301 above.

[0217] Step S804: The server determines the status information of the first detection device based on the channel data of the first detection device.

[0218] The status information includes abnormal alarm information and / or calibration parameters. Abnormal alarm information indicates an abnormal channel status of the first detection device, for example, an abnormal alarm message such as "The channel status of the first detection device is abnormal." Calibration parameters indicate the abnormal channel status of the first detection device and are used to calibrate the channels of the first detection device; for example, calibration parameters can reduce the deviation between the channel data of the first detection device and normal data to fall within a first value range.

[0219] Optionally, the server may determine the status information of the first detection device based solely on the channel data of the first detection device, without using the channel data of other detection devices.

[0220] Alternatively, the server may jointly determine the status information of the first detection device based on the channel data of the first detection device and the channel data of other detection devices. For example, the server determines the status information of the first detection device based on the channel data of the first detection device and the channel data of at least two second detection devices.

[0221] Optionally, the channel data of at least two second detection devices can also be obtained by each of the at least two second detection devices and reported to the control device connected to each of the second detection devices. These control devices then send the channel data of at least two second detection devices to the server, allowing the server to obtain the channel data of at least two second detection devices. Similarly, each of the at least two second detection devices can filter points in the point cloud, and the control devices connected to each of the second detection devices can also filter points in the point cloud. Specific filtering operations can be found in the relevant descriptions above. For example, the server can obtain channel data from a control device (which may be referred to as a second control device for convenience) connected to a third detection device. The channel data of the third detection device is used to indicate the channel characteristics of the third detection device within a second time period, which includes the first time period. The third detection device belongs to the aforementioned at least two second detection devices. Thus, channel data is added to the uplink interface between the third detection device and the second control device, and also to the uplink interface between the second control device and the server, so that the server can evaluate the channel status of the detection devices based on the channel data.

[0222] As one possible implementation, the server can determine the status information of the first detection device based on the changes in the channel characteristics of the first detection device during the first time period and the changes in the channel characteristics of at least two second detection devices during the first time period.

[0223] For specific implementation details, please refer to the relevant description in step S302 above.

[0224] Step S805: The server sends status information to the control device.

[0225] For example, the server sends status information to the control device (i.e., the first control device mentioned above) connected to the first detection device.

[0226] Accordingly, the first control device receives status information from the server. Thus, status information is added to the downlink interface between the server and the first control device, allowing the user to promptly understand the channel status of the first detection device.

[0227] For example, after receiving the status information, the first control device can display alarm information to the user. The alarm information is used to indicate that there is an anomaly in the detection information of the detection device, such as the alarm information being "the channel status of the first detection device is abnormal, and the current detection information of the detection device may be incorrect". Optionally, the first control device can display the alarm information on a screen or play the alarm information through a speaker.

[0228] Furthermore, when the first detection device is installed in a vehicle, the first control device can also disable some intelligent functions related to the detection information of the first detection device.

[0229] Step S806: The control device sends status information to the first detection device.

[0230] For example, a control device connected to the first detection device (i.e., the first control device mentioned above) sends status information to the first detection device.

[0231] Accordingly, the first detection device receives status information from the first control device. Thus, status information is added to the downlink interface between the first control device and the first detection device to facilitate the calibration of the first detection device's channel.

[0232] For example, when the status information includes calibration parameters, the first detection device can run a self-calibration function. For instance, the first detection device can calibrate the channel of the first detection device based on the calibration parameters, so that the deviation between the channel data of the first detection device and the normal data is reduced to fall within the first value range.

[0233] In the embodiment shown in Figure 8, the server can acquire channel data from the first detection device and determine whether the channel status of the first detection device is abnormal based on the channel data. The channel data of the first detection device is used to indicate the channel characteristics of the first detection device within a first time period. In this application, the server can comprehensively analyze the channel data of the detection device within a certain time period to perceive and evaluate abnormalities in the channel status of the detection device, effectively monitoring the channels of the detection device. Moreover, the server can identify abnormalities in the channel status of the detection device within a certain lifecycle, helping to promptly detect abnormal channel states and ensuring the reliability of the detection device's sensing capabilities. For example, if the first time period is the period from the manufacturing date of the first detection device to the current date, the server can monitor the channel status of the detection device throughout its entire lifecycle, improving the reliability of the detection device.

[0234] Especially in scenarios where the detection device is installed in a vehicle, the detection results are typically used for the vehicle's intelligent functions, such as intelligent driving systems, autonomous driving systems, and automatic parking systems. Utilizing the solution in this application can ensure the reliability of the vehicle's intelligent functions and improve user safety while riding in the vehicle.

[0235] Please refer to Figure 9, which is a flowchart illustrating another method for obtaining status information provided in this application embodiment. Optionally, this method for obtaining status information can be applied to the management system 20 shown in Figure 2a or Figure 2b. The method shown in Figure 9 includes at least the following steps:

[0236] Step S901: The processing device acquires channel data of the detection device belonging to the first product batch.

[0237] The processing device has data processing and communication capabilities, for example, the processing device is the processing device 102 shown in FIG2a or FIG2b.

[0238] The detection device has detection capabilities, and may be one of multiple detection devices (detection device 101a, detection device 101b, detection device 101n, etc.) as shown in Figure 2a or Figure 2b. Optionally, the detection device may be a lidar, millimeter-wave radar, centimeter-wave radar, or a fusion detection device, etc.

[0239] Detection devices belonging to the first product batch are those with the same model and all belonging to the first product batch. For example, in the management system 20, there are n detection devices among multiple detection devices. x of these n detection devices belong to the first product batch (e.g., detection devices 101a to 101x), and y of these n detection devices belong to the second product batch (e.g., detection devices 101y to 101n). Here, n, x, and y are all integers, and n, x, and y are all greater than 0. The sum of x and y is less than or equal to n. The detection devices belonging to the first product batch here include detection devices 101a to 101x from the multiple detection devices that belong to the first product batch.

[0240] The channel data of the detection devices belonging to the first product batch is used to indicate the channel characteristics of the detection devices belonging to the first product batch within a first time period. The first time period is a predefined or set time period, for example, the first time period may be the time period between the manufacturing time of the detection device and the current time. In one possible implementation, the channel data of the detection devices belonging to the first product batch includes characteristic data corresponding to the target point collected by each detection device in the first product batch through the channel within the first time period, and the characteristic data includes amplitude and / or phase.

[0241] Optionally, the channel data of the detection devices belonging to the first product batch can also be obtained by each detection device in the first product batch and then reported to the processing device. Similarly, each detection device in the first product batch can filter the points in the point cloud, and the processing device can also filter the points in the point cloud. For specific filtering operations, please refer to the relevant description in the aforementioned step S301.

[0242] Optionally, step S901 can be executed by the server; that is, some functions of the processing device are executed by the control device, and other functions are executed by the server. For example, the channel data of the detection devices belonging to the first product batch can be obtained by each detection device in the first product batch and reported to the control device connected to each detection device. These control devices then send the channel data of the detection devices belonging to the first product batch to the server, thereby allowing the server to obtain the channel data of the detection devices belonging to the first product batch.

[0243] Step S902: The processing device determines the status information based on the channel data of the detection device belonging to the first product batch.

[0244] The status information is used to indicate whether the channel status of the detection device belonging to the first product batch is abnormal.

[0245] Optionally, the processing device may determine the status information of the detection devices belonging to the first product batch based solely on the channel data of the detection devices belonging to the first product batch, without using the channel data of the detection devices belonging to other product batches. Alternatively, the processing device may determine the status information of the detection devices belonging to the first product batch based on both the channel data of the detection devices belonging to the first product batch and the channel data of the detection devices belonging to other product batches. These two implementation methods are described below.

[0246] In one implementation method, the processing device can determine the status information of the detection devices belonging to the first product batch based solely on the channel data of the detection devices belonging to the first product batch.

[0247] For example, the detection devices belonging to the first product batch include multiple detection devices. When the change in the channel characteristics of one of the multiple detection devices deviates from the changes in the channel characteristics of other detection devices within the first time period by a number equal to or greater than a preset quantity threshold, the status information is used to indicate that the channel status of the detection devices belonging to the first product batch is abnormal. The quantity threshold is a pre-set or predefined threshold, which may be related to the number of detection devices belonging to the first product batch, for example, 40, 50, etc. For example, the detection devices belonging to the first product batch include 100 detection devices, and the preset quantity threshold is 40. When there are 40 or more detection devices among these 100 detection devices whose changes in channel characteristics deviate from the changes in channel characteristics of other detection devices within the first time period, the status information is used to indicate that the channel status of the detection devices belonging to the first product batch is abnormal. When the channel characteristics of multiple detection devices deviate from the channel characteristics of other detection devices in the same time period by a number equal to or greater than a preset threshold, it can be considered that the channel status of this batch of detection devices is very likely to be abnormal. Subsequently, the manufacturer of the detection devices can be notified of the abnormality, so that the manufacturer can be informed of the channel status of a certain batch of detection devices in a timely manner and give early warning of potential network problems.

[0248] In the second implementation method, the processing device can jointly determine the status information of the detection device belonging to the first product batch based on the channel data of the detection device belonging to the first product batch and the channel data of the detection devices belonging to other product batches.

[0249] For example, the processing device determines the status information of the detection devices belonging to the first product batch based on channel data of detection devices belonging to the first product batch and channel data of detection devices belonging to the second product batch. The detection devices belonging to the second product batch are of the same model as those belonging to the first product batch, but from different batches. Similarly, the channel data of the detection devices belonging to the second product batch includes characteristic data corresponding to the target point collected by the detection devices belonging to the second product batch through the channel during a first time period, and the characteristic data includes amplitude and / or phase.

[0250] Optionally, the channel data of the detection devices belonging to the second product batch can also be obtained by each detection device in the second product batch and then reported to the processing device.

[0251] Similarly, each detection device in the detection device belonging to the second product batch can filter the points in the point cloud, and the processing device can also filter the points in the point cloud. For specific filtering operations, please refer to the relevant description in the aforementioned step S301.

[0252] In one possible implementation, the processing device can determine status information based on changes in the channel characteristics of a detection device belonging to a first product batch within a first time period and changes in the channel characteristics of a detection device belonging to a second product batch within the same time period. For example, when the changes in the channel characteristics of a detection device belonging to the first product batch within the first time period deviate from the changes in the channel characteristics of a detection device belonging to the second product batch within the same time period, the status information is used to indicate an abnormal channel status for the detection device belonging to the first product batch.

[0253] Referring to Figure 10, the channel characteristics of the detection devices belonging to the first product batch show an upward trend (or gradual deterioration) during the first time period, while the channel characteristics of the detection devices belonging to the second product batch show a stable trend. The channel characteristics of the detection devices belonging to the first product batch deviate significantly from those of the detection devices belonging to the second product batch during the first time period. The status information indicates abnormal channel status of the detection devices belonging to the first product batch. Thus, the above implementation method can monitor the differences in channel status between detection devices from different product batches, effectively monitor the channels of the entire batch of detection devices, and help provide early warning of potential network problems.

[0254] Optionally, step S902 can be executed by the server. After obtaining the channel data of the detection devices belonging to the first product batch, the server can determine the status information based on the channel data of the detection devices belonging to the first product batch. For specific implementation methods, please refer to the relevant descriptions above.

[0255] Optionally, the processing device may send status information. For example, the processing device sends status information to a management device. The processing device is connected to the management device. The management device is a device with communication capabilities, such as management device 104 in the management system shown in Figure 2a or Figure 2b. Optionally, the management device may be equipment used by the manufacturer of the detection device belonging to the first product batch (e.g., equipment used by product maintenance personnel).

[0256] Accordingly, the management equipment receives status information from the processing device, and the personnel using the management equipment can determine a solution strategy for channel status anomalies of the detection devices belonging to the first product batch based on the status information, such as recalling all detection devices belonging to the first product batch.

[0257] Optionally, the processing device may be a server. After determining the status information based on the channel data of the detection device belonging to the first product batch, the server may send the status information to the management device connected to the server.

[0258] In the embodiment shown in Figure 9, the processing device can determine whether the channel status of the detection devices belonging to the first product batch is abnormal based on the channel data of the detection devices belonging to the first product batch. This can effectively monitor the channels of the entire batch of detection devices and help to provide early warning of potential network problems.

[0259] The methods of the embodiments of this application have been described in detail above. Below, some apparatuses for implementing the foregoing methods are described. It should be understood that the division of units in the apparatuses provided in the embodiments of this application is only a logical functional division; in actual implementation, they can be fully or partially integrated onto a single physical entity, or they can be physically separated.

[0260] Furthermore, the units or modules in the device can be implemented in the form of processor calling software. For example, the device includes a processor connected to a memory, which stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of each unit of the device. The processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is either internal or external to the device.

[0261] Alternatively, the units or modules in the device can be implemented in the form of hardware circuits. The functionality of some or all units can be achieved through the design of these hardware circuits, which can be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC), and the functionality of some or all of the above units is achieved through the design of the logical relationships between the components within the circuit. In another implementation, the hardware circuit can be implemented using a programmable logic device (PLD), such as a field-programmable gate array (FPGA). This PLD can include a large number of logic gates, and the connection relationships between these logic gates can be configured through configuration files to achieve the functionality of some or all of the above units. All units of the above device can be implemented entirely through processor-invoked software, entirely through hardware circuits, or partially through processor-invoked software with the remaining parts implemented through hardware circuits.

[0262] In this application embodiment, a processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction read and execute capabilities, such as a central processing unit (CPU) or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. These logical relationships are fixed or reconfigurable. For example, the processor is a hardware circuit implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. Therefore, each unit in the device can be one or more processors (or processing circuits) configured to implement the above methods, such as a CPU, GPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor types.

[0263] Furthermore, the units or modules in the above devices can be integrated in whole or in part, or they can be implemented independently. In one implementation, these units or modules are integrated together as a system-on-a-chip (SOC). The SOC may include at least one processor for implementing any of the above methods or implementing the functions of the units in the device. The at least one processor may be of different types, such as CPU and FPGA.

[0264] Several possible devices are listed below.

[0265] Please refer to Figure 11, which is a schematic diagram of a processing device provided in an embodiment of this application, namely processing device 110. Optionally, the processing device 110 can be an independent device, such as the processing device 102 shown in Figure 1a. Alternatively, the processing device 110 can also be a component in an independent device (such as a node), such as a chip or integrated circuit. The processing device 110 is used to execute the steps performed by the processing device in the state information acquisition method shown in Figure 3. Alternatively, the processing device 110 can be the processing device 102 shown in Figure 1b, and the processing device 110 is used to execute the steps performed by the server in the state information acquisition method shown in Figure 8.

[0266] As shown in Figure 11, the processing device 110 includes a transceiver unit 1101 and a processing unit 1102. The transceiver unit 1101 is used to perform one or more operations such as acquiring, receiving, listening, transmitting, and sending, for example, acquiring channel data of the first detection device and sending status information. The channel data of the first detection device is used to indicate the channel characteristics of the first detection device within a first time period, and the status information is used to indicate whether the channel status of the first detection device is abnormal. It further includes other operations for implementing the status information acquisition method.

[0267] The processing unit 1102 is used to perform one or more operations such as processing, calculation, determination, generation, and updating, for example, to determine the status information of the first detection device based on the channel data of the first detection device. It further includes other operations for implementing the status information acquisition method.

[0268] For related descriptions, please refer to the descriptions of the embodiments shown in Figure 3 or Figure 8, which will not be described in detail here.

[0269] Please refer to Figure 12, which is a schematic diagram of another processing device provided in an embodiment of this application, namely processing device 120. Optionally, the processing device 120 can be an independent device, such as the processing device 102 shown in Figure 2a or Figure 2b. Alternatively, the processing device 120 can also be a component in an independent device (such as a node), such as a chip or integrated circuit. The processing device 120 is used to execute the steps performed by the control device or server in the state information acquisition method shown in Figure 9 above.

[0270] As shown in Figure 12, the processing device 120 includes a transceiver unit 1201 and a processing unit 1202. The transceiver unit 1201 is used to perform one or more operations such as acquiring, receiving, listening, transmitting, and sending. For example, it is used to acquire channel data of the detection devices belonging to the first product batch and send status information. The channel data of the detection devices belonging to the first product batch is used to indicate the channel characteristics of the detection devices belonging to the first product batch within a first time period, and the status information is used to indicate whether the channel status of the detection devices belonging to the first product batch is abnormal. It further includes other operations for implementing the status information acquisition method.

[0271] The processing unit 1202 is used to perform one or more operations such as processing, calculation, determination, generation, and updating, for example, to determine status information based on channel data of the detection device belonging to the first product batch. It further includes other operations for implementing the status information acquisition method.

[0272] For related descriptions, please refer to the description of the embodiment shown in Figure 9, which will not be described in detail here.

[0273] Please refer to Figure 13, which is a schematic diagram of another processing device provided in an embodiment of this application, namely processing device 130. Optionally, the processing device 130 can be an independent device, such as the control device 103 shown in Figure 1b. Alternatively, the processing device 130 can be multiple control devices (e.g., control device 103a, control device 103b, control device 103n, etc.) shown in Figure 2b. Alternatively, the processing device 130 can also be a device in an independent device (such as a node), such as a chip or integrated circuit. The processing device 130 is used to execute the steps performed by the control device in the state information acquisition method shown in Figure 8 above.

[0274] As shown in Figure 13, the processing device 130 includes a transceiver unit 1301. The transceiver unit 1301 is used to acquire channel data from the first detection device, send the channel data from the first detection device to the server, receive status information from the server, and send status information to the first detection device. The channel data from the first detection device is used to indicate the channel characteristics of the first detection device within a first time period, and the status information is used to indicate whether the channel status of the first detection device is abnormal. It further includes other operations for implementing the status information acquisition method.

[0275] Furthermore, the processing device 130 also includes a processing unit 1302. The processing unit 1302 is used to perform one or more operations such as processing, calculation, determination, generation, and updating. For example, it is used to determine the channel data of the first detection device based on the candidate channel data of the first detection device. The candidate channel data includes characteristic data corresponding to candidate points collected by the first detection device through the channels within a first time period, and the target point is a candidate point that meets a preset first condition. The device also includes other operations for implementing the state information acquisition method.

[0276] For related descriptions, please refer to the description of the embodiment shown in Figure 8, which will not be described in detail here.

[0277] Please refer to Figure 14, which is a schematic diagram of another processing device provided in an embodiment of this application, namely processing device 140. Optionally, the processing device 140 can be an independent device, such as the detection device 101 shown in Figure 1a or Figure 1b. Alternatively, the processing device 140 can be multiple detection devices (e.g., detection device 101a, detection device 101b, detection device 101n, etc.) shown in Figure 2a or Figure 2b. Alternatively, the processing device 140 can also be a device in an independent device (such as a node), such as a chip or integrated circuit. The processing device 140 is used to execute the steps performed by the detection device in the state information acquisition method shown in Figures 3, 8, or 9 above.

[0278] As shown in Figure 14, the processing device 140 includes a transceiver unit 1401. The transceiver unit 1401 is used to acquire channel data from the first detection device, send the channel data from the first detection device to the control device, and receive status information from the control device. The channel data from the first detection device is used to indicate the channel characteristics of the first detection device within a first time period, and the status information is used to indicate whether the channel status of the first detection device is abnormal. The device further includes other operations for implementing the status information acquisition method.

[0279] Furthermore, the processing device 140 also includes a processing unit 1402. The processing unit 1402 is used to perform one or more operations such as processing, calculation, determination, generation, and updating. For example, it is used to determine the channel data of the first detection device based on the initial channel data of the first detection device. The initial channel data includes characteristic data corresponding to initial points collected by the first detection device through the channel within a first time period, and the target point is an initial point among the initial points that satisfies a preset second condition. It further includes other operations for implementing the state information acquisition method.

[0280] For related descriptions, please refer to the descriptions of the embodiments shown in Figures 3, 8, or 9, which will not be described in detail here.

[0281] Please refer to Figure 15, which is a schematic diagram of the structure of a server provided in an embodiment of this application. The server is connected to a control device. A server is a device with processing capabilities. This device can be a physical device, such as a host, or a virtual device, such as a virtual machine or a container.

[0282] As shown in Figure 15, server 150 includes a processor 1501, a memory 1502, and one or more programs, and may include a communication interface 1503. It should be understood that this application does not limit the number of processors and memories in server 150.

[0283] Processor 1501 is a module for performing calculations and may include a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), a digital signal processor (DSP), a micro controller unit (MCU), or one or more integrated circuits for controlling the execution of programs in the above schemes.

[0284] Memory 1502 provides storage space, in which application data, user data, operating system, and computer programs can be optionally stored. Memory 1502 may include read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, random access memory (RAM) or other types of dynamic storage devices capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0285] The memory 1502 can exist independently and be connected to the processor 1501 via a bus. Alternatively, the memory 1502 can be integrated with the processor 1501.

[0286] The communication interface 1503 is used to provide information input or output to the at least one processor. And / or, the communication interface 1503 can be used to receive data transmitted externally and / or transmit data externally. The communication interface 1503 can be a wired link interface, including an Ethernet cable, or a wireless link interface (Bluetooth, general wireless transmission, and other wireless communication technologies, etc.). Optionally, the communication interface 1503 may also include a transmitter (such as a radio frequency transmitter, antenna, etc.) or a receiver coupled to the interface.

[0287] In this embodiment, one or more programs are stored in the memory 1502 in the form of program code and configured to be executed by the processor 1501. The programs include instructions for implementing the steps executed by the processing device in the state information acquisition method shown in FIG3 or FIG9, or instructions for implementing the steps executed by the server in the state information acquisition method shown in FIG8. That is, the memory 1502 stores executable instructions, and the processor 1501 executes these executable instructions to implement the method implemented by the processing device in the state information acquisition method shown in FIG3 or FIG9, or to implement the method implemented by the server in the state information acquisition method shown in FIG8. In other words, the memory 1502 stores instructions for executing the steps executed by the processing device in the state information acquisition method shown in FIG3 or 9, or instructions for implementing the steps executed by the server in the state information acquisition method shown in FIG8.

[0288] Please refer to Figure 16, which is a schematic diagram of a control device provided in an embodiment of this application. The control device is connected to the detection device and to the server. The control device is a device with processing capabilities. This device can be a physical device, such as a server or host, or a virtual device, such as a virtual machine or container.

[0289] As shown in Figure 16, the control device 160 includes a processor 1601, a memory 1602, and one or more programs, and may include a communication interface 1603. It should be understood that this application does not limit the number of processors and memories in the control device 160.

[0290] The processor 1601 is a module that performs calculations and may include a CPU, GPU, MP, DSP, MCU, or one or more integrated circuits used to control the execution of programs in the above scheme.

[0291] Memory 1602 provides storage space, in which application data, user data, operating system, and computer programs can be optionally stored. Memory 1602 may include ROM or other types of static storage devices capable of storing static information and instructions, RAM or other types of dynamic storage devices capable of storing information and instructions, or it may be EEPROM, CD-ROM or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0292] The memory 1602 can exist independently and be connected to the processor 1601 via a bus. Alternatively, the memory 1602 can be integrated with the processor 1601.

[0293] The communication interface 1603 is used to provide information input or output to the at least one processor. And / or, the communication interface 1603 can be used to receive data transmitted externally and / or transmit data externally. The communication interface 1603 can be a wired link interface, such as an Ethernet cable, or a wireless link interface (Bluetooth, general wireless transmission, and other wireless communication technologies, etc.). Optionally, the communication interface 1603 may also include a transmitter (such as a radio frequency transmitter, antenna, etc.) or a receiver coupled to the interface.

[0294] In this embodiment, one or more programs are stored in the memory 1602 in the form of program code and configured to be executed by the processor 1601. The programs include instructions for implementing the steps performed by the control device in the state information acquisition method shown in FIG8. That is, the memory 1602 stores executable instructions, and the processor 1601 executes these executable instructions to implement the method implemented by the control device in the state information acquisition method shown in FIG8. In other words, the memory 1602 stores instructions for executing the steps performed by the control device in the state information acquisition method shown in FIG8.

[0295] Please refer to Figure 17, which is a schematic diagram of a detection device provided in an embodiment of this application. The detection device is connected to a control device. The detection device is a device with detection and processing capabilities, such as radar or lidar.

[0296] As shown in Figure 17, the detection device 170 includes a processor 1701, a memory 1702, and one or more programs, and may include a communication interface 1703. It should be understood that this application does not limit the number of processors and memories in the detection device 170.

[0297] The processor 1701 is a module that performs calculations and may include a CPU, GPU, MP, DSP, MCU, or one or more integrated circuits used to control the execution of programs in the above scheme.

[0298] Memory 1702 provides storage space, in which application data, user data, operating system, and computer programs can be optionally stored. Memory 1702 may include ROM or other types of static storage devices capable of storing static information and instructions, RAM or other types of dynamic storage devices capable of storing information and instructions, or it may be EEPROM, CD-ROM or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0299] The memory 1702 can exist independently and be connected to the processor 1701 via a bus. Alternatively, the memory 1702 can be integrated with the processor 1701.

[0300] The communication interface 1703 is used to provide information input or output to the at least one processor. And / or, the communication interface 1703 can be used to receive data transmitted externally and / or transmit data externally. The communication interface 1703 can be a wired link interface, such as an Ethernet cable, or a wireless link interface (Bluetooth, general wireless transmission, and other wireless communication technologies, etc.). Optionally, the communication interface 1703 may also include a transmitter (such as a radio frequency transmitter, antenna, etc.) or a receiver coupled to the interface.

[0301] In this embodiment, one or more programs are stored in the memory 1702 in the form of program code and configured to be executed by the processor 1701. The programs include instructions for implementing the steps performed by the first detection device in the state information acquisition method shown in Figures 3, 8, and 9. That is, the memory 1702 stores executable instructions, and the processor 1701 executes these executable instructions to implement the method implemented by the first detection device in the state information acquisition method shown in Figures 3, 8, and 9. In other words, the memory 1702 stores instructions for executing the steps performed by the first detection device in the state information acquisition method shown in Figures 3, 8, and 9.

[0302] This application also provides a computer program product containing computer instructions. The computer program product may be a software or program product containing computer instructions, capable of running on a computing device or stored on any usable medium. When the computer instructions are executed by a processor, the aforementioned state information acquisition method is implemented, such as the state information acquisition method shown in Figures 3, 8, and 9.

[0303] This application also provides a computer-readable storage medium. This computer-readable storage medium is used to store a computer program, the computer program including instructions for implementing the aforementioned state information acquisition method, such as the state information acquisition method shown in Figures 3, 8, and 9.

[0304] The computer-readable storage medium can be any usable medium that can be stored by any of the following devices: processing device, control device, server, or detection device; or a data storage device such as a data center containing one or more usable media. The usable medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium, or a semiconductor medium (e.g., a solid-state drive).

[0305] In this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0306] In this application, "at least one" in the embodiments refers to one or more items, and "more than one" refers to two or more items. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can represent: a, b, c, (a and b), (a and c), (b and c), or (a and b and c), where a, b, and c can be single or multiple. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0307] Furthermore, unless otherwise stated, the use of ordinal numbers such as "first" and "second" in the embodiments of this application is for distinguishing multiple objects and is not for limiting the order, sequence, priority or importance of multiple objects.

[0308] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0309] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of this application.

Claims

1. A method for acquiring state information, characterized in that, The method includes: Acquire channel data of the first detection device, wherein the channel data of the first detection device is used to indicate the channel characteristics of the first detection device in a first time period; Based on the channel data of the first detection device, the status information of the first detection device is determined, and the status information is used to indicate whether the channel status of the first detection device is abnormal.

2. The method according to claim 1, characterized in that, The channel data of the first detection device includes characteristic data of the target point collected by the first detection device through the channel during the first time period, and the characteristic data includes amplitude and / or phase.

3. The method according to claim 1 or 2, characterized in that, The method is applied to a server connected to a first control device, wherein acquiring the channel data of the first detection device includes: Acquire channel data from a first detection device connected to the first control device.

4. The method according to claim 3, characterized in that, The method further includes: The status information is sent to the first control device.

5. The method according to any one of claims 1-4, characterized in that, The status information includes abnormal alarm information and / or calibration parameters; The abnormal alarm information is used to indicate that the channel status of the first detection device is abnormal; The calibration parameters are used to indicate abnormal channel status of the first detection device and to calibrate the channels of the first detection device.

6. The method according to any one of claims 1-5, characterized in that, The determination of the status information of the first detection device based on the channel data of the first detection device includes: Based on the channel data of the first detection device and the channel data of at least two second detection devices, determine the status information of the first detection device; The channel data of the at least two second detection devices are used to indicate the channel characteristics of the at least two second detection devices during the first time period, and the at least two second detection devices are of the same model as the first detection device.

7. The method according to claim 6, characterized in that, The method is applied to a server connected to a second control device, and the method further includes: Acquire channel data from a third detection device connected to the second control device, the channel data of the third detection device being used to indicate the channel characteristics of the third detection device during a second time period, the second time period including the first time period; The third detection device is one of the at least two second detection devices.

8. The method according to claim 6 or 7, characterized in that, The determination of the status information of the first detection device based on the channel data of the first detection device and the channel data of at least two second detection devices includes: Based on the changes in the channel characteristics of the first detection device during the first time period and the changes in the channel characteristics of the at least two second detection devices during the first time period, the state information of the first detection device is determined.

9. The method according to claim 8, characterized in that, When the deviation between the channel characteristics of the first detection device during the first time period and the channel characteristics of the at least two second detection devices during the first time period meets a predefined abnormal condition, the status information is used to indicate that the channel status of the first detection device is abnormal.

10. The method according to claim 9, characterized in that, The abnormal conditions include abrupt abnormal conditions and non-abrupt abnormal conditions. The abrupt abnormal conditions indicate that the change in the channel characteristics of the first detection device during the first time period deviates suddenly from the change in the channel characteristics of the at least two second detection devices during the first time period.

11. The method according to any one of claims 1 to 5, characterized in that, The first time period includes multiple sub-time periods. When the change in the channel characteristics of the first detection device in the first sub-time period deviates from the change in the channel characteristics of the first detection device in other sub-time periods, the status information is used to indicate that the channel status of the first detection device is abnormal. The first sub-time period belongs to the multiple sub-time periods, and the other sub-time periods are at least two sub-time periods other than the first sub-time period among the multiple sub-time periods.

12. A state information acquisition method characterized by comprising: The method includes: Acquire channel data of the detection device belonging to the first product batch, wherein the channel data of the detection device belonging to the first product batch is used to indicate the channel characteristics of the detection device belonging to the first product batch in a first time period; Based on the channel data of the detection device belonging to the first product batch, status information is determined, which is used to indicate whether the channel status of the detection device belonging to the first product batch is abnormal.

13. The method of claim 12, wherein, The channel data of the detection device belonging to the first product batch includes the characteristic data of the target point collected by the detection device belonging to the first product batch through the channel during the first time period, and the characteristic data includes amplitude and / or phase.

14. The method according to claim 12 or 13, characterized in that, The determination of status information based on the channel data of the detection device belonging to the first product batch includes: The status information is determined based on the channel data of the detection device belonging to the first product batch and the channel data of the detection device belonging to the second product batch; The detection device belonging to the second product batch is the same model as the detection device belonging to the first product batch, but from a different batch.

15. The method of claim 14, wherein, The determination of the status information based on the channel data of the detection device belonging to the first product batch and the channel data of the detection device belonging to the second product batch includes: The status information is determined based on the changes in the channel characteristics of the detection device belonging to the first product batch during the first time period and the changes in the channel characteristics of the detection device belonging to the second product batch during the first time period.

16. The method of claim 15, wherein, When the channel characteristics of the detection device belonging to the first product batch deviate from the channel characteristics of the detection device belonging to the second product batch during the first time period, the status information is used to indicate that the channel status of the detection device belonging to the first product batch is abnormal.

17. A state information acquisition method characterized by comprising: The method, applied to a control device connected to a first detection device, includes: Acquire channel data of the first detection device, wherein the channel data of the first detection device is used to indicate the channel characteristics of the first detection device in a first time period; Send the channel data of the first detection device to the server; Receive status information from the server, the status information being used to indicate whether the channel status of the first detection device is abnormal; The status information is sent to the first detection device.

18. The method of claim 17, wherein, The channel data of the first detection device includes characteristic data of the target point collected by the first detection device through the channel during the first time period, and the characteristic data includes amplitude and / or phase.

19. The method of claim 17 or 18, wherein, The status information includes abnormal alarm information and / or calibration parameters; The abnormal alarm information is used to indicate that the channel status of the first detection device is abnormal; The calibration parameters are used to indicate abnormal channel status of the first detection device and to calibrate the channels of the first detection device.

20. The method according to any one of claims 17-19, characterized by, The acquisition of channel data from the first detection device includes: Receive the channel data of the first detection device reported by the first detection device.

21. The method of claim 18, wherein, The acquisition of channel data from the first detection device includes: The system receives alternative channel data reported by the first detection device, wherein the alternative channel data includes characteristic data corresponding to alternative points collected by the first detection device through the channel during the first time period. Based on the candidate channel data of the first detection device, the channel data of the first detection device is determined, and the target point is the candidate point among the candidate points that meets the preset first condition.

22. The method of claim 21, wherein, The first condition includes at least one of the following: The number of target objects in the point cloud satisfies a preset quantity condition and / or a preset distance condition. The preset distance condition is used to constrain the distance between the target object and the first detection device. The point cloud includes a plurality of candidate points. The point cloud was collected in a scenario that met the preset scenario conditions.

23. The method of claim 22, wherein, The number of target objects in the point cloud satisfies a preset quantity condition and / or a preset distance condition, including: the target objects in the point cloud are isolated target objects and the isolated target objects are located within a first distance range.

24. A state information acquisition method characterized by comprising: The method, applied to a first detection device connected to a control device, includes: Acquire channel data of the first detection device, wherein the channel data of the first detection device is used to indicate the channel characteristics of the first detection device in a first time period; Send the channel data of the first detection device to the control device; The status information received from the control device is used to indicate whether the channel status of the first detection device is abnormal.

25. The method of claim 24, wherein, The channel data of the first detection device includes characteristic data of the target point collected by the first detection device through the channel during the first time period, and the characteristic data includes amplitude and / or phase.

26. The method of claim 24 or 25, wherein, The status information includes abnormal alarm information and / or calibration parameters; The abnormal alarm information is used to indicate that the channel status of the first detection device is abnormal; The calibration parameters are used to indicate abnormal channel status of the first detection device and to calibrate the channels of the first detection device.

27. The method of claim 25, wherein, The acquisition of channel data from the first detection device includes: Acquire the initial channel data of the first detection device, wherein the initial channel data includes characteristic data corresponding to the initial point collected by the first detection device through the channel within a first time period; Based on the initial channel data of the first detection device, the channel data of the first detection device is determined, and the target point is the initial point among the initial points that meets the preset second condition.

28. The method of claim 27, wherein, The second condition includes at least one of the following: the signal-to-noise ratio of the point cloud falls within a first range, the first detection device has no abnormal reporting flag, the azimuth angle of the point cloud falls within a first angle range, the pitch angle of the point cloud falls within a second angle range, the target object in the point cloud is located within a second distance range, and the point cloud includes multiple initial points.

29. A processing device, comprising: The processing apparatus includes a transceiver unit and a processing unit, the transceiver unit and the processing unit being used to perform the method as described in any one of claims 1-28.

30. A server, characterized in that, The server is connected to a control device. The server includes a processor and a memory. The memory stores a program. The processor executes the program to cause the server to implement the method as described in any one of claims 1-16.

31. A detection device, characterized in that, The detection device is connected to a control device. The detection device includes a processor and a memory. The memory stores a program. The processor executes the program to enable the detection device to perform the method as described in any one of claims 24-28.

32. A control device, characterized in that, The control device is connected to a server and a detection device. The control device includes a processor and a memory. The memory stores a program, and the processor executes the program to enable the control device to implement the method as described in any one of claims 17-23.

33. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program, the computer program including instructions for performing the method as described in any one of claims 1-28.

34. A computer program product, characterized in that, The computer program product includes instructions that, when executed by a processor, cause the method as described in any one of claims 1-28 to be implemented.

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