Measurement data processing method and device, vehicle-mounted inertial measurement device and vehicle

Abstract

The invention relates to the technical field of data processing, and discloses a measured data processing method and device, a vehicle-mounted inertial measurement device and a vehicle, the method is applied to a vehicle-mounted controller of the vehicle-mounted inertial measurement device, and the vehicle-mounted inertial measurement device integrates an inertial measurement unit and the vehicle-mounted controller. The method comprises the following steps: acquiring original measurement data acquired by an inertial measurement unit through a serial bus; configuring a corresponding target timestamp for the original measurement data; correcting the original measurement data to generate corrected target measurement data; and executing corresponding processing according to the target measurement data with the target timestamp. According to the invention, the vehicle-mounted controller directly carries out sampling and data processing on the inertial measurement unit, the data delay is relatively low, and the cost can be saved; the accuracy of the timestamp and the accuracy of the data can be guaranteed, and vehicle control can be conveniently achieved based on the high-precision timestamp and measurement data.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to methods and apparatus for processing measurement data, vehicle-mounted inertial measurement devices, and vehicles. Background Technology

[0002] An IMU (Inertial Measurement Unit) is a motion sensor that measures triaxial acceleration and triaxial angular velocity. In autonomous driving systems, IMUs provide high-frequency motion data, capturing rapid changes in vehicle movement. By fusing this data with image data from cameras and point cloud data from LiDAR, vehicle motion prediction and positioning can be achieved.

[0003] Currently, the IMU modules used in vehicles are stand-alone. These stand-alone IMU modules consist of an MPU (Microprocessor Unit) and an IMU. The MPU processes the data collected by the IMU before sending it to the vehicle controller, resulting in relatively large data delays. Summary of the Invention

[0004] In view of this, the present invention provides a method, apparatus, vehicle-mounted inertial measurement device, and vehicle for processing measurement data, in order to solve the problem of large data delay in traditional IMUs.

[0005] In a first aspect, the present invention provides a method for processing measurement data, applied to an on-board controller of an on-board inertial measurement unit (IMU), wherein the IMU integrates an inertial measurement unit and the on-board controller, and the inertial measurement unit is connected to the on-board controller via a serial bus; the method includes:

[0006] The raw measurement data collected by the inertial measurement unit is obtained through the serial bus;

[0007] Configure a corresponding target timestamp for the raw measurement data;

[0008] The original measurement data is corrected to generate corrected target measurement data;

[0009] Perform corresponding processing based on the target measurement data with the target timestamp.

[0010] In some optional implementations, configuring a corresponding target timestamp for the raw measurement data includes:

[0011] Determine the original timestamp of the original measurement data;

[0012] The original timestamp is corrected to obtain the target timestamp corresponding to the original measurement data.

[0013] In some optional implementations, determining the original timestamp of the original measurement data includes:

[0014] Determine the first timestamp of the original measurement data sent by the inertial measurement unit to the vehicle controller;

[0015] Determine the second timestamp at which the vehicle controller acquires the original measurement data;

[0016] The original timestamp of the original measurement data is determined based on the first timestamp and the second timestamp.

[0017] In some optional implementations, the step of correcting the original timestamp to obtain the target timestamp corresponding to the original measurement data includes:

[0018] Linear fitting is performed based on the original timestamp and multiple historical timestamps within the historical time period to determine the functional relationship between the timestamp and the number of samplings; the historical timestamp is the timestamp corresponding to the historical measurement data collected by the inertial measurement unit within the historical time period;

[0019] The timestamp corresponding to the number of samplings of the original measurement data is determined according to the functional relationship, and the timestamp corresponding to the number of samplings of the original measurement data is used as the target timestamp corresponding to the original measurement data.

[0020] In some alternative implementations, the inertial measurement unit includes a storage unit that records calibration data for data correction.

[0021] The step of correcting the original measurement data to generate corrected target measurement data includes:

[0022] Read the calibration data from the storage unit;

[0023] The original measurement data is corrected based on the calibration data to generate corrected target measurement data.

[0024] In some optional implementations, the method further includes:

[0025] The vehicle controller is upgraded over the air to update the data correction algorithm;

[0026] The step of correcting the original measurement data based on the calibration data to generate corrected target measurement data includes:

[0027] The updated data correction algorithm is used to correct the original measurement data based on the calibration data, thereby generating corrected target measurement data.

[0028] In some optional implementations, acquiring the raw measurement data collected by the inertial measurement unit via the serial bus includes:

[0029] In response to an interrupt signal triggered by the inertial measurement unit to the vehicle controller, the raw measurement data collected by the inertial measurement unit is read through the serial bus.

[0030] Secondly, the present invention provides a measurement data processing device applied to an on-board controller of an on-board inertial measurement unit, wherein the on-board inertial measurement unit integrates an inertial measurement unit and the on-board controller, and the inertial measurement unit is connected to the on-board controller via a serial bus; the device includes:

[0031] The data acquisition module is used to acquire the raw measurement data collected by the inertial measurement unit through the serial bus;

[0032] The timestamp module is used to configure the corresponding target timestamp for the original measurement data;

[0033] The calibration module is used to calibrate the original measurement data and generate the calibrated target measurement data;

[0034] The processing module is used to perform corresponding processing based on the target measurement data with the target timestamp.

[0035] Thirdly, the present invention provides an inertial measurement device for vehicles, comprising an integrated inertial measurement unit and an inertial controller; the inertial measurement unit and the inertial controller are connected via a serial bus.

[0036] The vehicle controller is used to execute the measurement data processing method of the first aspect or any corresponding embodiment described above.

[0037] Fourthly, the present invention provides a vehicle including the vehicle-mounted inertial measurement device of the third aspect above or any corresponding embodiment thereof.

[0038] Fifthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the measurement data processing method of the first aspect or any corresponding embodiment described above.

[0039] In a sixth aspect, the present invention provides a computer program product, including computer instructions for causing a computer to execute the measurement data processing method of the first aspect or any corresponding embodiment thereof.

[0040] This invention enables the onboard controller to directly sample and process data from the inertial measurement unit (IMU). The two communicate via a high-speed serial bus, allowing the onboard controller to quickly acquire measurement data with low latency. Furthermore, since the onboard controller processes the measurement data, a separate MPU is not required, saving costs. The onboard controller determines the timestamp of the measurement data, effectively utilizing its high-precision timer system, which ensures timestamp accuracy. The onboard controller's processing power is used to correct the measurement data, further guaranteeing the data's accuracy and facilitating vehicle control based on high-precision timestamps and measurement data. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of the present invention, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0042] Figure 1 This is a schematic diagram illustrating the working principle of a stand-alone IMU module;

[0043] Figure 2 This is a schematic diagram of a vehicle-mounted inertial measurement device according to an embodiment of the present invention;

[0044] Figure 3 This is a flowchart illustrating a method for processing measurement data according to an embodiment of the present invention;

[0045] Figure 4 This is a flowchart illustrating another method for processing measurement data according to an embodiment of the present invention;

[0046] Figure 5 This is a schematic diagram of a functional relationship according to an embodiment of the present invention;

[0047] Figure 6 This is another structural schematic diagram of the vehicle-mounted inertial measurement device according to an embodiment of the present invention;

[0048] Figure 7 This is a structural block diagram of a measurement data processing apparatus according to an embodiment of the present invention;

[0049] Figure 8 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] The IMU modules used in vehicles are generally commercially available stand-alone devices, such as... Figure 1 As shown, this stand-alone IMU module includes an MPU (Micro Processor Unit) and an IMU. The MPU performs preliminary processing on the high-frequency sampled data from the IMU and then forwards it to the vehicle controller via the CAN (Controller Area Network) bus. The vehicle controller can then use this IMU data. Figure 1 As shown, the vehicle controller can be implemented based on an MCU (Microcontroller Unit) or a SOC (System on Chip); if the SOC does not support the CAN bus, an additional MCU that supports the CAN bus can be set up.

[0052] Standalone IMU modules typically connect to onboard controllers such as the autonomous driving main control SOC system via a CAN bus. This results in the raw measurement data collected by the IMU needing to be processed remotely and then output and forwarded via the CAN bus before reaching the SOC side, leading to significant data latency. Furthermore, standalone IMU modules require a separate MPU for initial data processing, which is also costly.

[0053] This invention provides a method for processing measurement data by integrating an inertial measurement unit (IMU) with an onboard controller. The onboard controller performs sampling and data processing for the IMU without the need for an additional MPU, which not only improves data transmission efficiency but also reduces costs.

[0054] According to an embodiment of the present invention, a method for processing measurement data is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0055] This embodiment provides a method for processing measurement data, applied to the vehicle controller of an inertial measurement unit, which integrates an inertial measurement unit and the vehicle controller. Figure 2A schematic diagram of one structure of the vehicle-mounted inertial measurement device is shown, such as... Figure 2 As shown, the inertial measurement unit 201 and the vehicle controller 202 are connected via a serial bus for communication. Figure 2 The example shown is the SPI (Serial Peripheral Interface) bus. SPI enables high-speed intra-board communication.

[0056] Figure 3 This is a flowchart of a method for processing measurement data according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps.

[0057] Step S301: Obtain the raw measurement data collected by the inertial measurement unit via the serial bus.

[0058] In this embodiment, the inertial measurement unit 201 and the vehicle controller 202 are integrated together and can be connected via a serial bus such as SPI to achieve high-speed data transmission. The inertial measurement unit 201 can be a sensor used to collect motion parameters such as acceleration or angular velocity, and it does not have processing capabilities itself; for example, the inertial measurement unit 201 can be an IMU in a stand-alone IMU module that is only used for data collection. The vehicle controller 202 is the controller in the vehicle that needs to use IMU-related data, such as an autonomous driving main control SOC; the vehicle controller 202 can be implemented based on an MCU or an SOC, and this embodiment does not limit this.

[0059] During operation, the inertial measurement unit 201 performs measurements in real time (periodically) and collects corresponding measurement data. For example, when this vehicle-mounted inertial measurement device is installed on a vehicle, the inertial measurement unit 201 can collect motion parameters such as the vehicle's acceleration or angular velocity; these motion parameters are the measurement data. For ease of description, the measurement data collected by the inertial measurement unit 201 is referred to as raw measurement data.

[0060] Specifically, the vehicle controller 202 can obtain the raw measurement data acquired by the inertial measurement unit 201 based on the serial bus between the two, enabling the vehicle controller 202 to read the raw measurement data at high speed and achieve high-frequency sampling.

[0061] Step S302: Configure the corresponding target timestamp for the raw measurement data.

[0062] In this embodiment, the inertial measurement unit 201 is only used to collect raw measurement data in real time, and the corresponding timestamp can be determined using the high-precision timer system of the vehicle controller 202 itself. Specifically, after the vehicle controller 202 obtains the raw measurement data, it can configure a suitable timestamp, i.e., the target timestamp, for the raw measurement data.

[0063] Step S303: Correct the original measurement data to generate corrected target measurement data.

[0064] In this embodiment, the inertial measurement unit 201 is easily affected by various factors when collecting data. In order to ensure the accuracy of the collected data, the vehicle controller 202 can use its powerful processing capabilities to correct the original measurement data and generate corrected data, i.e., target measurement data.

[0065] For example, when the inertial measurement unit 201 collects measurement data, it is easily affected by temperature. Therefore, after obtaining the original measurement data, it is necessary to perform temperature compensation. The compensated data is temperature-independent measurement data, which can more accurately represent the motion state of the vehicle. This measurement data can be used as the target measurement data.

[0066] Step S304: Perform corresponding processing based on the target measurement data with the target timestamp.

[0067] In this embodiment, after processing the raw measurement data collected by the inertial measurement unit 201 as described above, the vehicle controller 202 can determine the accurate target measurement data and the configured target timestamp (because the raw measurement data and the target measurement data are in one-to-one correspondence, the target timestamp configured for the raw measurement data is also the timestamp of the target measurement data). The target measurement data can represent the vehicle's motion state (e.g., acceleration, angular velocity), and the target timestamp can represent the specific time the vehicle is in that motion state. Using the target measurement data with the target timestamp, the vehicle controller 202 can perform the corresponding processing.

[0068] For example, the vehicle controller 202 can determine the vehicle's motion state in real time based on target measurement data with a target timestamp, thereby enabling vehicle control, such as achieving autonomous driving or assisted driving. Alternatively, the vehicle controller 202 can also send the target measurement data with a target timestamp to other algorithm modules of the vehicle controller 202, or to other controllers, via inter-process communication or external networks (such as CAN bus), so that other entities can use the target measurement data.

[0069] It is understood that the vehicle controller 202 can periodically acquire raw measurement data. For example, the vehicle controller 202 can acquire raw measurement data from the inertial measurement unit 201 at regular intervals (e.g., 1ms). For each set of raw measurement data, the vehicle controller 202 can determine the target timestamp and target measurement data based on the same processing method described above, which will not be elaborated upon in this embodiment.

[0070] The measurement data processing method provided in this embodiment allows the onboard controller to directly sample and process data from the inertial measurement unit (IMU). The two communicate via a high-speed serial bus, enabling the onboard controller to quickly acquire measurement data with low latency. Furthermore, since the onboard controller processes the measurement data, a separate MPU is not required, saving costs. The onboard controller determines the timestamp of the measurement data, effectively utilizing its high-precision timer system, which ensures the accuracy of the timestamp. The processing power of the onboard controller is used to correct the measurement data, further ensuring the accuracy of the data itself. This facilitates vehicle control based on high-precision timestamps and measurement data.

[0071] This embodiment provides a method for processing measurement data, applied to the vehicle controller of an inertial measurement unit, wherein the inertial measurement unit specifically integrates an inertial measurement unit and the vehicle controller. Figure 4 This is a flowchart of a method for processing measurement data according to an embodiment of the present invention, such as... Figure 4 As shown, the process includes the following steps.

[0072] Step S401: Obtain the raw measurement data collected by the inertial measurement unit via the serial bus.

[0073] Please see details Figure 3 Step S301 of the illustrated embodiment will not be described again here.

[0074] In some optional implementations, step S401, "acquiring the raw measurement data collected by the inertial measurement unit via the serial bus," may specifically include: in response to an interrupt signal triggered by the inertial measurement unit to the vehicle controller, reading the raw measurement data collected by the inertial measurement unit via the serial bus.

[0075] In this embodiment, after the inertial measurement unit 201 acquires the raw measurement data, it actively triggers a corresponding interrupt signal to the vehicle controller 202. Upon receiving the interrupt signal, the vehicle controller 202 determines that there is raw measurement data to be read, and thus directly reads the raw measurement data through the serial bus between the two. Furthermore, after the raw measurement data in the inertial measurement unit 201 is read, the inertial measurement unit 201 continues to acquire raw measurement data for the next moment, and so on.

[0076] The inertial measurement unit 201 may be equipped with a register or buffer for temporarily storing the original measurement data. After receiving the interrupt signal, the vehicle controller 202 can directly read the register or buffer to read the current original measurement data.

[0077] In this embodiment, the inertial measurement unit 201 triggers an interrupt signal, enabling the vehicle controller 202 to acquire the original measurement data in a timely manner. Furthermore, when the vehicle controller 202 reads the original measurement data, the inertial measurement unit 201 can stop measuring, that is, the inertial measurement unit 201 does not write data at this time, which can effectively avoid data read and write conflicts.

[0078] Step S402: Configure the corresponding target timestamp for the raw measurement data.

[0079] Specifically, step S402, "configuring the corresponding target timestamp for the raw measurement data", includes the following steps.

[0080] Step S4021: Determine the original timestamp of the original measurement data.

[0081] In this embodiment, when the vehicle controller 202 acquires the raw measurement data, it can directly determine the timestamp of the raw measurement data. For ease of description, the directly determined timestamp is referred to as the raw timestamp. For example, the vehicle controller 202 can directly use the timestamp when it reads the raw measurement data as the raw timestamp.

[0082] Optionally, step S4021, "determine the original timestamp of the original measurement data", may include steps A1 to A3.

[0083] Step A1: Determine the first timestamp of the inertial measurement unit sending the raw measurement data to the vehicle controller.

[0084] Step A2: Determine the second timestamp of the original measurement data obtained by the vehicle controller.

[0085] Step A3: Determine the original timestamp of the original measurement data based on the first timestamp and the second timestamp.

[0086] In this embodiment, the vehicle controller 202 can directly determine two timestamps related to the original measurement data. One is the timestamp corresponding to the original measurement data sent by the inertial measurement unit 201 to the vehicle controller 202, which is the first timestamp; the other is the timestamp of the original measurement data obtained by the vehicle controller 202, which is the second timestamp.

[0087] For example, if the vehicle controller 202 reads the original measurement data based on the interrupt signal triggered by the inertial measurement unit 201, the vehicle controller 202 can use the timestamp of receiving the interrupt signal as the first timestamp. Furthermore, the timestamp at which the vehicle controller 202 completely reads the original measurement data from the inertial measurement unit 201 can be used as the second timestamp.

[0088] After determining the first and second timestamps, the vehicle controller 202 can determine the timestamp of the original measurement data by combining the first and second timestamps, and use the timestamp determined at this time as the original timestamp.

[0089] The original timestamp is the timestamp between the first timestamp and the second timestamp. For example, the average of the first timestamp and the second timestamp can be used as the original timestamp; or, the first timestamp and the second timestamp can be weighted and the weighted result can be used as the original timestamp.

[0090] Step S4022: Correct the original timestamp to obtain the target timestamp corresponding to the original measurement data.

[0091] In this embodiment, the vehicle controller 202 differs from a traditional MPU in that it needs to handle multiple tasks. As a result, the original timestamp directly determined by the vehicle controller 202 may be affected by system load fluctuations or operating system scheduling delays, leading to a certain error in the determined original timestamp. Based on this, this embodiment also corrects the original timestamp, thereby reducing the impact of system load fluctuations on the timestamp and ensuring that a more accurate target timestamp can be obtained.

[0092] In some optional implementations, the above step S4022, "correcting the original timestamp to obtain the target timestamp corresponding to the original measurement data", may include steps B1 to B2.

[0093] Step B1: Perform linear fitting based on the original timestamp and multiple historical timestamps within the historical time period to determine the functional relationship between the timestamp and the number of samplings; the historical timestamp is the timestamp corresponding to the historical measurement data collected by the inertial measurement unit within the historical time period.

[0094] Step B2: Determine the timestamp corresponding to the number of samplings of the original measurement data based on the functional relationship, and use the timestamp corresponding to the number of samplings of the original measurement data as the target timestamp of the original measurement data.

[0095] In this embodiment, since the vehicle controller 202 can periodically acquire the measurement data collected by the inertial measurement unit 201, the vehicle controller 202 can acquire multiple previously collected measurement data, i.e., historical measurement data, within the previous historical time period. Each historical measurement data also has a corresponding timestamp, i.e., a historical timestamp. The historical timestamp of the historical measurement data can be a directly obtained timestamp (which is a kind of original timestamp) or a corrected timestamp (which is a kind of target timestamp). This embodiment does not limit this.

[0096] Within a previous historical time period, multiple historical timestamps can be identified, and linear fitting can then be performed based on these historical timestamps. To ensure a good fit, historical timestamps that are closer to the original timestamp are preferred; for example, if the historical time period is the closest to the original timestamp, then each historical timestamp is also one of the most recent historical timestamps.

[0097] Both the original timestamp and the historical timestamps are determined by a single sampling. Therefore, each timestamp corresponds to a specific number of samplings. Thus, for each timestamp, a corresponding two-dimensional array (number of samplings, timestamp) can be generated based on its corresponding number of samplings. Linear fitting can then be performed based on multiple two-dimensional arrays to ultimately determine the functional relationship between the timestamp and the number of samplings. This functional relationship can be understood as a linear function, i.e., y = kx + b, where x represents the number of samplings, y represents the timestamp, k is the slope of the function, and b is the intercept of the function.

[0098] Since the original measurement data corresponds to the number of samplings, after determining the functional relationship, the timestamp corresponding to the number of samplings of the original measurement data can be determined based on the functional relationship, and this timestamp can be used as the target timestamp corresponding to the original measurement data.

[0099] Figure 5 A schematic diagram of this functional relationship is shown, such as... Figure 5 As shown, taking the measurement data corresponding to sampling times 1 to 6 as an example, the 6th sampling is the latest sampling, that is, the timestamp t6 corresponding to sampling time 6 is the original timestamp. After determining the functional relationship y = kx + b, that is, after determining the parameters k and b, the timestamp t6' when the sampling time is 6 (i.e., x = 6) can be determined based on this functional relationship, which is the target timestamp. Therefore, after correcting the timestamp through this functional relationship, the timestamp of the corresponding original measurement data can be corrected from the original timestamp t6 to the target timestamp t6'.

[0100] In this embodiment, linear fitting using multiple timestamps can quickly and easily determine the sampling pattern of the timestamps, thereby enabling accurate correction of the timestamps and ensuring the accuracy of the target timestamp.

[0101] Step S403: Correct the original measurement data to generate corrected target measurement data.

[0102] Please see details Figure 3 Step S303 of the illustrated embodiment will not be described again here.

[0103] In some alternative implementations, the inertial measurement unit includes a storage unit that records calibration data for data correction. Figure 6 Another structural schematic diagram of an onboard inertial measurement unit is shown, such as... Figure 6 As shown, the inertial measurement unit 201 includes an acquisition unit 2011 and a storage unit 2012. The acquisition unit 2011 is used to perform acquisition functions and may be, for example, an IMU (Insulated Measurement Unit). The storage unit 2012 may be, for example, Flash memory, and is used to store calibration data required for correction. This calibration data may include, for example, offset values ​​for correcting temperature drift or error matrices for correcting inherent system errors; this embodiment does not limit the specific data.

[0104] Furthermore, the aforementioned step S403, "correcting the original measurement data and generating corrected target measurement data," may include steps C1 to C2.

[0105] Step C1: Read calibration data from the storage unit.

[0106] Step C2: Correct the original measurement data based on the calibration data to generate the corrected target measurement data.

[0107] In this embodiment, the inertial measurement unit 201 can store calibration data, enabling the vehicle controller 202 to read the calibration data and correct the original measurement data based on the calibration data. The inertial measurement unit 201 integrates a data acquisition unit 2011 and a storage unit 2012 for storing the calibration data. The inertial measurement unit 201 can be a board structure with a pluggable design for easy replacement.

[0108] like Figure 6 As shown, the vehicle controller 202 may specifically include a data sampling unit 2021, a data processing unit 2022, and a control configuration unit 2023.

[0109] The control configuration unit 2023 is used to initialize the inertial measurement unit 201 when powered on and read the calibration data in the storage unit 2012.

[0110] The data sampling unit 2021 implements precise high-frequency sampling of IMU measurement data through the SPI bus and determines the timestamp of the measurement data. Specifically, it requires the support of the high-precision timer system and interrupt system on the vehicle controller 202.

[0111] The data processing unit 2022 is responsible for processing the output data of the data sampling unit 2021. It can utilize the powerful computing power of the SOC / MCU to correct the original measurement data, such as by averaging filtering, data correction compensation, and data temperature compensation, so as to obtain the target measurement data that meets the requirements of the downstream algorithm module and make the measurement data more accurate.

[0112] like Figure 6 As shown, the vehicle controller 202 may also include a data publishing unit 2024, which is responsible for the final data publishing and can send the target measurement data to other algorithm modules that need it through inter-process communication or network.

[0113] Optionally, the method further includes: performing an over-the-air upgrade on the vehicle controller to update the data correction algorithm.

[0114] Furthermore, step C2 above, "correcting the original measurement data based on the calibration data to generate corrected target measurement data," can specifically include: using an updated data correction algorithm to correct the original measurement data based on the calibration data to generate corrected target measurement data.

[0115] In this embodiment, the vehicle controller 202 supports over-the-air (OTA) updates. When updating the firmware of the vehicle controller 202 based on OTA technology, if it is necessary to update the calibration algorithm for the measurement data, the data calibration algorithm in the vehicle controller 202 can be updated based on OTA technology. For example, the Kalman filter algorithm can be updated, or when performing calibration based on data fitting, the specific fitting algorithm can be updated.

[0116] After acquiring the raw measurement data, the data can be corrected using the latest data correction algorithm. The correction process is based on the calibration data, and the final result is accurate target measurement data.

[0117] In this embodiment, the inertial measurement unit 201 pre-records calibration data for correction, which can be obtained by pre-calibrating the inertial measurement unit 201. Based on this calibration data, the raw measurement data collected by the inertial measurement unit 201 can be specifically corrected to ensure the accuracy of the final data. Furthermore, taking advantage of the over-the-air upgrade feature of the vehicle controller 202, the data correction algorithm can be dynamically updated.

[0118] Step S404: Perform corresponding processing based on the target measurement data with the target timestamp.

[0119] Please see details Figure 3 Step S304 of the illustrated embodiment will not be described again here.

[0120] The measurement data processing method provided in this embodiment does not require a stand-alone IMU device and is independent of the MPU, which not only reduces costs but also avoids transmission delays, ensuring data transmission and processing efficiency. The original timestamp directly determined from the raw measurement data is corrected, thereby reducing the impact of system load fluctuations on the timestamp caused by the vehicle controller and ensuring a relatively accurate target timestamp. Using linear fitting with multiple timestamps, the sampling pattern of the timestamps can be determined simply and quickly, enabling accurate correction of the timestamps and ensuring the precision of the target timestamp.

[0121] This embodiment also provides a measurement data processing apparatus for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0122] This embodiment provides a measurement data processing device applied to the vehicle controller of an inertial measurement unit (IMU). The IMU integrates an inertial measurement unit and the vehicle controller, and the inertial measurement unit is connected to the vehicle controller via a serial bus. Figure 7 As shown, the device includes:

[0123] The data acquisition module 701 is used to acquire the raw measurement data collected by the inertial measurement unit through the serial bus;

[0124] The timestamp module 702 is used to configure a corresponding target timestamp for the original measurement data;

[0125] The calibration module 703 is used to calibrate the original measurement data and generate the calibrated target measurement data;

[0126] The processing module 704 is used to perform corresponding processing based on the target measurement data with the target timestamp.

[0127] In some optional implementations, the timestamp module 702 configures a corresponding target timestamp for the raw measurement data, including:

[0128] Determine the original timestamp of the original measurement data;

[0129] The original timestamp is corrected to obtain the target timestamp corresponding to the original measurement data.

[0130] In some optional implementations, the timestamp module 702 determines the original timestamp of the original measurement data, including:

[0131] Determine the first timestamp of the original measurement data sent by the inertial measurement unit to the vehicle controller;

[0132] Determine the second timestamp at which the vehicle controller acquires the original measurement data;

[0133] The original timestamp of the original measurement data is determined based on the first timestamp and the second timestamp.

[0134] In some optional implementations, the timestamp module 702 corrects the original timestamp to obtain a target timestamp corresponding to the original measurement data, including:

[0135] Linear fitting is performed based on the original timestamp and multiple historical timestamps within the historical time period to determine the functional relationship between the timestamp and the number of samplings; the historical timestamp is the timestamp corresponding to the historical measurement data collected by the inertial measurement unit within the historical time period;

[0136] The timestamp corresponding to the number of samplings of the original measurement data is determined according to the functional relationship, and the timestamp corresponding to the number of samplings of the original measurement data is used as the target timestamp corresponding to the original measurement data.

[0137] In some alternative implementations, the inertial measurement unit includes a storage unit that records calibration data for data correction.

[0138] The correction module 703 corrects the original measurement data to generate corrected target measurement data, including:

[0139] Read the calibration data from the storage unit;

[0140] The original measurement data is corrected based on the calibration data to generate corrected target measurement data.

[0141] In some optional embodiments, the processing module 704 is further configured to:

[0142] The vehicle controller is upgraded over the air to update the data correction algorithm;

[0143] The correction module 703 corrects the original measurement data based on the calibration data to generate corrected target measurement data, including:

[0144] The updated data correction algorithm is used to correct the original measurement data based on the calibration data, thereby generating corrected target measurement data.

[0145] In some optional implementations, the data acquisition module 701 acquires the raw measurement data collected by the inertial measurement unit via the serial bus, including:

[0146] In response to an interrupt signal triggered by the inertial measurement unit to the vehicle controller, the raw measurement data collected by the inertial measurement unit is read through the serial bus.

[0147] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0148] In this embodiment, the measurement data processing device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, including a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0149] This invention also provides an in-vehicle inertial measurement unit (IMU), comprising an integrated IMU unit and an in-vehicle controller; the IMU unit and the in-vehicle controller are connected via a serial bus; the in-vehicle controller is used to execute the measurement data processing method provided in any of the above embodiments. For a detailed description of this in-vehicle IMU, please refer to... Figure 2 or Figure 6 The relevant descriptions are not elaborated here.

[0150] This invention also provides a vehicle including the aforementioned vehicle-mounted inertial measurement unit (IMU). Based on this IMU, vehicle motion parameters can be collected quickly and accurately, thereby optimizing vehicle control.

[0151] This invention also provides a computer device having the above-described features. Figure 7 The device for processing the measurement data shown; the computer device may be, for example, the vehicle controller described above.

[0152] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 8As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 8 Take a processor 10 as an example.

[0153] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0154] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0155] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0156] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0157] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0158] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0159] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0160] Although embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations should all be covered within the protection scope of the present invention.

Claims

1. A method for processing measurement data, characterized in that, An on-board controller for an inertial measurement unit (IMU), wherein the IMU integrates an inertial measurement unit and the on-board controller, and the inertial measurement unit is connected to the on-board controller via a serial bus; the method includes: The raw measurement data collected by the inertial measurement unit is obtained through the serial bus; Configure a corresponding target timestamp for the raw measurement data; The original measurement data is corrected to generate corrected target measurement data; Perform corresponding processing based on the target measurement data with the target timestamp.

2. The method according to claim 1, characterized in that, Configuring a corresponding target timestamp for the original measurement data includes: Determine the original timestamp of the original measurement data; The original timestamp is corrected to obtain the target timestamp corresponding to the original measurement data.

3. The method according to claim 2, characterized in that, Determining the original timestamp of the original measurement data includes: Determine the first timestamp of the original measurement data sent by the inertial measurement unit to the vehicle controller; Determine the second timestamp at which the vehicle controller acquires the original measurement data; The original timestamp of the original measurement data is determined based on the first timestamp and the second timestamp.

4. The method according to claim 2, characterized in that, The step of correcting the original timestamp to obtain the target timestamp corresponding to the original measurement data includes: Linear fitting is performed based on the original timestamp and multiple historical timestamps within the historical time period to determine the functional relationship between the timestamp and the number of samplings; the historical timestamp is the timestamp corresponding to the historical measurement data collected by the inertial measurement unit within the historical time period; The timestamp corresponding to the number of samplings of the original measurement data is determined according to the functional relationship, and the timestamp corresponding to the number of samplings of the original measurement data is used as the target timestamp corresponding to the original measurement data.

5. The method according to claim 1, characterized in that, The inertial measurement unit includes a storage unit that records calibration data for data correction. The step of correcting the original measurement data to generate corrected target measurement data includes: Read the calibration data from the storage unit; The original measurement data is corrected based on the calibration data to generate corrected target measurement data.

6. The method according to claim 5, characterized in that, The method further includes: The vehicle controller is upgraded over the air to update the data correction algorithm; The step of correcting the original measurement data based on the calibration data to generate corrected target measurement data includes: The updated data correction algorithm is used to correct the original measurement data based on the calibration data, thereby generating corrected target measurement data.

7. The method according to claim 1, characterized in that, The acquisition of the raw measurement data collected by the inertial measurement unit via the serial bus includes: In response to an interrupt signal triggered by the inertial measurement unit to the vehicle controller, the raw measurement data collected by the inertial measurement unit is read through the serial bus.

8. A device for processing measurement data, characterized in that, An on-board controller for an inertial measurement unit (IMU), wherein the IMU integrates an inertial measurement unit and the on-board controller, and the inertial measurement unit is connected to the on-board controller via a serial bus; the device includes: The data acquisition module is used to acquire the raw measurement data collected by the inertial measurement unit through the serial bus; The timestamp module is used to configure the corresponding target timestamp for the original measurement data; The calibration module is used to calibrate the original measurement data and generate the calibrated target measurement data; The processing module is used to perform corresponding processing based on the target measurement data with the target timestamp.

9. A vehicle-mounted inertial measurement device, characterized in that, It includes an integrated inertial measurement unit and an on-board controller; the inertial measurement unit and the on-board controller are connected via a serial bus; The vehicle controller is used to execute the measurement data processing method according to any one of claims 1 to 7.

10. A vehicle, characterized in that, Includes the vehicle-mounted inertial measurement device as described in claim 9.

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