Data acquisition and processing method and device for ultrasonic radar detection visual field and medium

Abstract

The invention provides a data acquisition and processing method and device for an ultrasonic radar detection visual field and a medium, and relates to the technical field of ultrasonic radars. The method comprises the steps that a plurality of radar probes are sequentially controlled to transmit signals so as to obtain the distance between the radar probes and an obstacle, the radar probes are deployed on a transverse shaft of calibration cloth, and the obstacle is located on a calibration point of the calibration cloth; based on the distance obtained when the obstacle is located at each calibration point, determining a first acquisition data set under the calibration cloth coordinate system, the first acquisition data set comprising a mapping relation among the coordinate of the obstacle, the coordinate of the radar probe and the distance; and for each radar probe, taking the radar probe as an original point, and converting the obstacle coordinates mapped by the coordinates of the radar probe in the first acquisition data set to obtain a second acquisition data set under the radar probe coordinate system. According to the invention, the plurality of radar probes are automatically controlled to work cooperatively, so that the detection data of the plurality of radar probes can be acquired at the same time in one-time data acquisition, and the data acquisition efficiency is remarkably improved.

Description

Technical Field

[0001] The present application relates to the field of ultrasonic radar technology, and in particular to a method, device and medium for collecting and processing data of an ultrasonic radar detection field. Background Art

[0002] Ultrasonic radar has been widely used in the field of industrial vehicles due to its mature technology and controllable cost, especially in parking and collision avoidance systems. As the core component of these systems, the performance of the ultrasonic radar probe directly affects the overall effect of these systems. Usually, the manufacturer of the radar probe needs to provide the collected data of the detection field of view so that the vehicle manufacturer can reasonably arrange the position of the radar probe on the vehicle based on this collected data.

[0003] In the related art, a single radar probe is usually installed on a test platform, and a calibration object such as a polyvinyl chloride (PVC) water pipe of a specific size is used to simulate an obstacle. The obstacle is moved on the grid of the calibration cloth by manpower, and the data returned by the radar probe after each movement is manually recorded. In this way, the data collected by the ultrasonic radar detection field is obtained. However, there is a problem of low data collection efficiency. Summary of the invention

[0004] The embodiments of the present application provide a method, device and medium for collecting and processing data of an ultrasonic radar detection field of view, so as to improve the efficiency of data collection of an ultrasonic radar detection field of view in related technologies.

[0005] In a first aspect, an embodiment of the present application provides a method for collecting and processing data of an ultrasonic radar detection field of view, comprising:

[0006] Control multiple radar probes to transmit signals in sequence to obtain the distance between the corresponding radar probe and the obstacle. The radar probes are deployed on the horizontal axis of the calibration cloth, and the obstacle is located at the calibration point of the calibration cloth.

[0007] Based on the distances obtained when the obstacles are located at each calibration point, a first acquisition data set in the calibration coordinate system is determined, where the first acquisition data set includes a mapping relationship between the obstacle coordinates, the radar probe coordinates, and the distances;

[0008] For each radar probe, the radar probe is taken as the origin, and according to the coordinates of the radar probe, in the first acquisition data set, the coordinates of the obstacle mapped by the coordinates of the radar probe are transformed to obtain a second acquisition data set in the radar probe coordinate system.

[0009] In a possible implementation, the width of each grid in the calibration cloth is a set length, and the remainders of the distances between different radar probes and the origin of the calibration cloth divided by the set length are different.

[0010] In a possible implementation, the calibration point is a grid endpoint in the calibration cloth. Before the obstacle coordinates mapped by the coordinates of the radar probe are converted, it also includes: determining whether there are target obstacle coordinates that are not grid endpoint coordinates in the obstacle coordinates of the obstacle; if there are target obstacle coordinates, then in the first acquisition data set, deleting the target obstacle coordinates and the distance mapped to the target obstacle coordinates.

[0011] In a possible implementation, the multiple radar probes are target model radar probes, and the multiple radar probes are controlled in sequence to transmit signals, including: within a set time period, the multiple radar probes are controlled in sequence to periodically transmit signals.

[0012] In a possible implementation, the data acquisition and processing method for the ultrasonic radar detection field of view also includes: for each obstacle coordinate in the second acquisition data set, determining the steady-state statistical information of multiple distances corresponding to the obstacle coordinates, the steady-state statistical information including the maximum value, minimum value and average value of the multiple distances; based on the steady-state statistical information corresponding to each obstacle coordinate in the second acquisition data set, establishing a data model, the data model reflects the performance parameters of the radar probe of the target model, the performance parameters including the probe missed detection rate, the actual detectable range, the stable feedback value and the fluctuation of the detection data.

[0013] In a possible implementation, the data acquisition and processing method of the ultrasonic radar detection field of view also includes at least one of the following: controlling the radar probe to rotate a set angle along the center line of the radar probe to obtain the performance parameters of the target model radar probe in the vertical range; based on the data models corresponding to the different models of radar probes, obtaining the lateral comparison results of the different models of radar probes; based on the performance parameters of the target model radar probe, determining the vehicle layout plan of the target model's combination of multiple radar probes.

[0014] In a possible implementation, the data acquisition and processing method of the ultrasonic radar detection field of view also includes: determining the positional relationship between the target obstacle and the target vehicle based on the distance between the radar probe and the obstacle; and / or establishing a dynamic positional relationship between the target obstacle and the target vehicle based on the distance between the radar probe and the obstacle, and simulating to obtain the real-time distance between the radar probe and the obstacle corresponding to different positional relationships.

[0015] In a second aspect, the present application provides a data acquisition and processing device for ultrasonic radar detection field of view, comprising:

[0016] A control module is used to control multiple radar probes to transmit signals in sequence to obtain the distance between the corresponding radar probe and the obstacle, the radar probes are deployed on the horizontal axis of the calibration cloth, and the obstacle is located at the calibration point of the calibration cloth;

[0017] A determination module, used to determine a first acquisition data set in a calibration coordinate system based on the distance obtained when the obstacle is located at each calibration point, wherein the first acquisition data set includes a mapping relationship between the obstacle coordinates, the radar probe coordinates and the distance;

[0018] The processing module is used to transform the coordinates of obstacles mapped by the coordinates of the radar probe in the first acquisition data set according to the coordinates of the radar probe, taking the radar probe as the origin, and obtain a second acquisition data set in the radar probe coordinate system.

[0019] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0020] Memory for storing computer-executable instructions;

[0021] A processor, configured to execute computer-executable instructions stored in a memory to implement any one of the methods described in the first aspect.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed, they are used to implement any of the methods in the first aspect.

[0023] In a fifth aspect, the present application provides a computer program product, including a computer program, which implements any method in the first aspect when executed.

[0024] The data acquisition and processing method, device and medium of the ultrasonic radar detection field provided by the present application sequentially control multiple radar probes to transmit signals to obtain the distance between the corresponding radar probe and the obstacle, wherein the radar probe is deployed on the horizontal axis of the calibration cloth, and the obstacle is located at the calibration point of the calibration cloth; based on the distance obtained when the obstacle is located at each calibration point, determine the first acquisition data set in the calibration cloth coordinate system, the first acquisition data set contains the mapping relationship between the obstacle coordinates, the coordinates of the radar probe and the distance; for each radar probe, take the radar probe as the origin, and according to the coordinates of the radar probe, in the first acquisition data set, perform coordinate conversion on the obstacle coordinates mapped by the coordinates of the radar probe, and obtain the second acquisition data set in the radar probe coordinate system. In this process, by automatically controlling multiple radar probes to work together, and converting the acquisition data sets in the calibration cloth coordinate system corresponding to the multiple radar probes into the acquisition data sets in the radar probe coordinate system, the detection data of multiple radar probes can be obtained simultaneously in one data acquisition, which significantly improves the efficiency of data acquisition compared with the traditional method of measuring one by one by a single radar probe. In addition, by automatically controlling multiple radar probes, the intervention of manual operation is reduced, the human error in the data acquisition process is reduced, and the accuracy of the data is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0026] Figure 1 A schematic diagram of an application scenario of a method for collecting and processing data from an ultrasonic radar detection field of view provided by an exemplary embodiment of the present application;

[0027] Figure 2 A schematic diagram of a flow chart of a method for collecting and processing data of an ultrasonic radar detection field of view provided by an exemplary embodiment of the present application;

[0028] Figure 3 A schematic diagram of the deployment and detection results of multiple radar probes provided for an exemplary embodiment of the present application;

[0029] Figure 4 A schematic diagram of coordinate transformation provided for an exemplary embodiment of the present application;

[0030] Figure 5 A schematic diagram of performance parameters of a radar probe provided for an exemplary embodiment of the present application;

[0031] Figure 6 A schematic diagram of the detection area of ​​a radar probe in a vertical range and stable feedback values ​​of each area provided by an exemplary embodiment of the present application;

[0032] Figure 7 A schematic diagram comparing the performance parameters of a radar probe of target model 1 and a radar probe of target model 2 provided in an exemplary embodiment of the present application;

[0033] Figure 8 A schematic diagram of a vehicle layout scheme of a plurality of radar probe combinations provided for an exemplary embodiment of the present application;

[0034] Fig. 9 Another schematic diagram of a flow chart of a method for collecting and processing data of an ultrasonic radar detection field of view provided by an exemplary embodiment of the present application;

[0035] Fig.10 A schematic diagram of a structure of a data acquisition and processing device for ultrasonic radar detection field of view provided by an exemplary embodiment of the present application;

[0036] Fig.11 A schematic diagram of the structure of an electronic device provided for an exemplary embodiment of the present application.

[0037] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0038] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0039] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable in appropriate circumstances, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, the process, system, product or equipment comprising a series of steps or units need not be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, products or equipment.

[0040] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0041] In the related art, it is necessary to rely on manual recording of the detection data returned by the radar probe after each movement, and only the detection data of a single radar probe can be obtained; if more detection data is to be obtained, the collection process needs to be repeated to obtain the collection data of the ultrasonic radar detection field of view, resulting in low efficiency in data collection.

[0042] In order to solve the above problems, the embodiment of the present application provides a data collection and processing solution for the detection field of view of ultrasonic radar, by deploying multiple radar probes side by side on the horizontal axis of the calibration cloth, controlling the multiple radar probes to transmit signals in sequence, so as to obtain the distance between the corresponding radar probe and the obstacle, thereby obtaining the collection data set in the calibration cloth coordinate system; and converting the collection data set in the calibration cloth coordinate system corresponding to the multiple radar probes into the collection data set in the radar probe coordinate system, so as to obtain the detection data of multiple radar probes at the same time in one data collection, which significantly improves the efficiency of data collection. In addition, by automatically controlling multiple radar probes, the intervention of manual operation is reduced, the human error in the data collection process is reduced, and the accuracy of the data is improved.

[0043] Figure 1 Schematic diagram of an application scenario of the data collection and processing method of the ultrasonic radar detection field of view provided by the exemplary embodiment of the present application. Figure 1 As shown, the application scenario includes a client 11, a server 12 and a radar probe 13, wherein the number of the client 11 can be at least one, and the number of the radar probe 13 can be at least one. In practical applications, when the server 12 detects the data collection instruction submitted by the client 11, it executes the data collection and processing method of the ultrasonic radar detection field provided in the present application to obtain a collection data set in the radar probe coordinate system.

[0044] It should be noted that the server 12 can also be replaced by a server cluster or other computing devices with certain computing power, and the client 11 can be a computer and a notebook, etc., which is not limited here.

[0045] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0046] Figure 2 A flow chart of a method for collecting and processing data from ultrasonic radar detection field of view provided by an exemplary embodiment of the present application. Figure 2 As shown, the data collection and processing method of the ultrasonic radar detection field of view includes the following steps:

[0047] S201. Control multiple radar probes to transmit signals in sequence to obtain the distance between the corresponding radar probes and obstacles. The radar probes are deployed on the horizontal axis of the calibration cloth, and the obstacles are located at the calibration points of the calibration cloth.

[0048] For example, according to the maximum detection range of the radar probe, select or design a calibration cloth on the ground. The longitudinal length and lateral width of the calibration cloth should cover the maximum detection range of the radar probe; place the obstacle at a calibration point on the calibration cloth. The obstacle can be a PVC water pipe with a diameter of 75 mm or objects of other sizes and types. Establish a coordinate system based on the calibration cloth. Specifically, the bottom width of the calibration cloth is used as the X-axis, and the center O of the bottom edge is the origin of the coordinate system; the left side of the X-axis is negative and the right side is positive; the vertical length of the calibration cloth is used as the Y-axis, O is the origin and the Y-axis has only positive direction; define the calibration points on the calibration cloth (that is, the placement position of the obstacle) according to the test requirements. Further deploy multiple radar probes on the X-axis of the calibration cloth, such as Figure 3 As shown, multiple radar probes, such as radar probe A, radar probe B, radar probe C and radar probe D, are deployed on the X-axis of the calibration cloth. The lateral distance between each radar probe and the origin O is recorded as Xa, Xb, Xc, and Xd. The coordinates of the four radar probes in the calibration cloth coordinate system are (-Xa, 0), (-Xb, 0), (Xc, 0) and (Xd, 0), respectively.

[0049] Correspondingly, multiple radar probes are controlled to transmit signals in sequence, and each radar probe receives a signal reflected from an obstacle after transmitting the signal, thereby obtaining the distance between each radar probe and the obstacle. By controlling multiple radar probes to transmit signals in sequence, the same-frequency interference between radar probes can be reduced, and the probability of generating erroneous data can be reduced; for example, Figure 3 As shown, when the coordinates of the obstacle are (X1, Y1), the distances between each radar probe and the obstacle are La1, Lb1, Lc1 and Ld1 respectively; further, the obstacle is moved to the next calibration point of the calibration cloth, and the distances between each radar probe and the obstacle are obtained again; after traversing all the calibration points on the calibration cloth, the data collection work is completed.

[0050] It should be noted that Figure 3 The four radar probes shown are only an example. In actual applications, 2, 4, 5, 8 or 10 radar probes can be deployed according to test requirements. There is no limit on the number of radar probes.

[0051] S202: Determine a first acquisition data set in a calibration coordinate system based on the distances obtained when the obstacles are located at each calibration point, where the first acquisition data set includes a mapping relationship between the obstacle coordinates, the radar probe coordinates, and the distances.

[0052] For example, based on the distances obtained when the obstacle is located at each calibration point, as well as the coordinates of the obstacle and the coordinates of the radar probe, a mapping relationship between the coordinates of the obstacle, the coordinates of the radar probe, and the distance is established. For example, when the coordinates of the obstacle are (X1, Y1), the associated four radar probe coordinates are (-Xa, 0), (-Xb, 0), (Xc, 0) and (Xd, 0), and the associated distances are La1, Lb1, Lc1 and Ld1; when the coordinates of the obstacle are (Xn, Yn), the associated four radar probe coordinates are (-Xa, 0), (-Xb, 0), (Xc, 0) and (Xd, 0), and the associated distances are Lan, Lbn, Lcn and Ldn, where n is a positive integer, indicating that the obstacle is located at the nth calibration point.

[0053] It should be noted that the obstacle coordinates may be manually entered or automatically entered by a target acquisition device, and the method for obtaining the obstacle coordinates is not limited here.

[0054] S203, for each radar probe, take the radar probe as the origin, and perform coordinate transformation on the obstacle coordinates mapped by the coordinates of the radar probe in the first acquisition data set according to the coordinates of the radar probe, so as to obtain a second acquisition data set in the radar probe coordinate system.

[0055] For example, radar probe A is taken as the origin, and according to the coordinates (-Xa, 0) of radar probe A, in the first acquisition data set, the coordinates of the obstacle (X1, Y1) mapped by the coordinates (-Xa, 0) of radar probe A are transformed, and the coordinates of the obstacle in the radar probe coordinate system are (X1+Xa, Y1); radar probe B is taken as the origin, and according to the coordinates (-Xb, 0) of radar probe B, in the first acquisition data set, the coordinates of the obstacle (X1, Y1) mapped by the coordinates (-Xb, 0) of radar probe B are transformed, and the coordinates of the obstacle in the radar probe coordinate system are (X1+Xb, Y1); take radar probe C as the origin, according to the coordinates (Xc, 0) of radar probe C, in the first acquisition data set, the coordinates of the obstacle (X1, Y1) mapped by the coordinates (Xc, 0) of radar probe C are transformed, and the obstacle coordinates in the radar probe coordinate system are (X1-Xc, Y1); take radar probe D as the origin, according to the coordinates (Xd, 0) of radar probe D, in the first acquisition data set, the coordinates of the obstacle (X1, Y1) mapped by the coordinates (Xd, 0) of radar probe D are transformed, and the obstacle coordinates in the radar probe coordinate system are (X1-Xd, Y1). For example, Figure 4 A schematic diagram of coordinate transformation provided for an exemplary embodiment of the present application. Figure 3 and Figure 4 ,against Figure 3The obstacle coordinates (X1, Y1) in the image can be converted into the mapping relationship between the four radar probes and one obstacle through coordinate transformation. Figure 4 The mapping relationship between one radar probe and four obstacles is shown, and after the coordinate transformation, the distance between the radar probe and the obstacle remains unchanged, which are La1, Lb1, Lc1 and Ld1 respectively. Further, in this way, in the first acquisition data set, the coordinates of each obstacle mapped by the coordinates of the radar probe are transformed to obtain the second acquisition data set in the radar probe coordinate system.

[0056] The data collection and processing method for ultrasonic radar detection field provided in the embodiment of the present application can obtain the detection data of multiple radar probes simultaneously in one data collection by automatically controlling multiple radar probes to work together and converting the collection data set in the calibration cloth coordinate system corresponding to the multiple radar probes into the collection data set in the radar probe coordinate system. Compared with the traditional method of measuring one radar probe one by one, the efficiency of data collection is significantly improved. In addition, by automatically controlling multiple radar probes, the intervention of manual operation is reduced, the human error in the data collection process is reduced, and the accuracy of the data is improved.

[0057] In some embodiments, the width of each grid in the calibration cloth is a set length, and the remainders of the distances between different radar probes and the origin of the calibration cloth divided by the set length are different.

[0058] For example, Figure 3 As shown, the width of each grid in the calibration cloth is a set length, such as Δ; accordingly, when multiple radar probes, such as radar probe A, radar probe B, radar probe C, and radar probe D, are deployed on the X-axis of the calibration cloth, it is necessary to ensure that the remainders of the distances between different radar probes and the origin of the calibration cloth divided by the set length are different, that is, the remainders of Xa, Xb, Xc, and Xd divided by Δ are different. Correspondingly, Figure 4 As shown, after coordinate transformation, some of the obstacle coordinates in the multiple obstacle coordinates corresponding to the radar probe as the origin are located between two calibration points, thereby achieving more fine-grained obstacle positioning.

[0059] In the embodiment of the present application, by ensuring that the remainders of the distances between different radar probes and the origin of the calibration cloth divided by the set length are different, the position of the obstacle can be located more accurately, thereby achieving finer-grained coordinate positioning.

[0060] Considering that the width of each grid in the calibration cloth is generally small, for example, 100mm×100mm, large errors may be introduced when placing obstacles manually, thereby affecting the accuracy of data collection. Therefore, in some embodiments, the calibration points are the grid endpoints in the calibration cloth, and before the coordinate transformation of the obstacle coordinates mapped by the radar probe is performed, it also includes: determining whether there are target obstacle coordinates that are not grid endpoint coordinates in the obstacle coordinates of the obstacles; if there are target obstacle coordinates, then in the first acquisition data set, the target obstacle coordinates and the distance that has a mapping relationship with the target obstacle coordinates are deleted.

[0061] For example, Figure 3 As shown, the calibration points are the grid endpoints in the calibration cloth. When the width of each grid is the set length, the coordinates of each grid endpoint are known; each time the obstacle is moved, the goal is to place the obstacle on the corresponding calibration point. If it is not placed in place, errors may be introduced, affecting the accuracy of data collection. Accordingly, assuming that the coordinates of each obstacle are (X1, Y1), (X2, Y2), (X3, Y3), ..., (Xn, Yn), it is determined in turn whether there are target obstacle coordinates that are not grid endpoint coordinates in each obstacle coordinate; if there are target obstacle coordinates such as (X2, Y2), then in the first acquisition data set, delete the target obstacle coordinates (X2, Y2) and the distances La2, Lb2, Lc2 and Ld2 that have a mapping relationship with (X2, Y2).

[0062] In the embodiment of the present application, by deleting the target obstacle coordinates and related data of non-grid endpoints, errors introduced by improper obstacle placement can be avoided, thereby ensuring the accuracy of data collection, improving the quality of the data set, and providing a reliable basis for coordinate transformation and data analysis.

[0063] In some embodiments, the multiple radar probes are target model radar probes, and the multiple radar probes are controlled to transmit signals in sequence, including: within a set time period, the multiple radar probes are controlled to transmit signals periodically in sequence.

[0064] For example, Figure 3 As shown, when the obstacle is located at the calibration point (X1, Y1), within a set time length, such as T minutes, multiple radar probes are controlled in sequence to transmit signals at set time intervals, wherein T can be, for example, 1, 5 or 10, and the time interval can be, for example, 50ms or 100ms; correspondingly, the distance between each radar probe and the obstacle, such as La1, Lb1, Lc1 and Ld1, is obtained. Through T minutes of data collection, a set of stable detection data fed back by each radar probe can be obtained when the obstacle is located at the calibration point (X1, Y1), such as La1, Lb1, Lc1 and Ld1 respectively represent a set of distance values.

[0065] In the embodiment of the present application, a set of stable detection data can be obtained by periodically transmitting signals within a set time period, thereby reducing the accidental errors that may be caused by a single acquisition and improving the reliability of the collected data; in addition, by obtaining stable detection data, the robustness and reliability in the face of complex environments and changing conditions can be improved.

[0066] Considering the low data collection efficiency in related technologies, and the difficulty of obtaining collected data to quantitatively and intuitively reflect the actual performance of radar probes, such as missed detection rate, actual detectable range, stable feedback value, and fluctuation of detection data, this limitation makes it difficult for vehicle manufacturers to effectively compare and select different models of radar products; in addition, the lack of digitized performance parameters also limits the further simulation of radar-related performance or functions. Therefore, how to digitize the performance parameters of radar probes can not only more accurately and intuitively reflect the actual performance of radar probes, but also provide reliable data support for radar selection, function adaptation and simulation, thereby improving the overall efficiency of development work and further promoting the application of ultrasonic radar in various fields.

[0067] Therefore, on the basis of the above embodiments, in some implementations, the data acquisition and processing method of the ultrasonic radar detection field of view also includes: for each obstacle coordinate in the second acquisition data set, determining the steady-state statistical information of multiple distances corresponding to the obstacle coordinates, the steady-state statistical information includes the maximum value, minimum value and average value of the multiple distances; based on the steady-state statistical information corresponding to each obstacle coordinate in the second acquisition data set, establishing a data model, the data model reflects the performance parameters of the radar probe of the target model, the performance parameters include the probe missed detection rate, the actual detectable range, the stable feedback value and the fluctuation of the detection data.

[0068] For example, in the calibration coordinate system, each calibration point corresponds to data collection for a set duration, such as T minutes; correspondingly, in the radar probe coordinate system, each obstacle coordinate corresponds to a distance value for a set duration, for example, La1, Lb1, Lc1 and Ld1 respectively correspond to arrays of distance values; by calculating the values ​​in each array, steady-state statistical information of multiple distances can be obtained. For example, by calculating the values ​​in the La1 array, the maximum value, minimum value and average value of all detection distances corresponding to the obstacle coordinates (X1+Xa, Y1) can be obtained; by calculating the values ​​in the Lb1 array, the maximum value, minimum value and average value of all detection distances corresponding to the obstacle coordinates (X1+Xb, Y1) can be obtained; by calculating the values ​​in the Lc1 array, the maximum value, minimum value and average value of all detection distances corresponding to the obstacle coordinates (X1-Xc, Y1) can be obtained; by calculating the values ​​in the Ld1 array, the maximum value, minimum value and average value of all detection distances corresponding to the obstacle coordinates (X1-Xd, Y1) can be obtained.

[0069] Correspondingly, the missed detection rate is calculated by analyzing which calibration points have not been detected in multiple acquisitions. Specifically, the ratio of the number of calibration points that have not been detected to the total number of calibration points can be counted; the actual detection range of the radar probe is determined by using the maximum and minimum values ​​corresponding to all obstacle coordinates. The maximum value represents the maximum detection distance of the radar probe under ideal conditions, and the minimum value represents the minimum detection capability of the radar probe under different conditions; the feedback value of the radar probe in a stable state is represented by using the average value of each obstacle coordinate, which reflects the typical detection result of the radar probe under normal working conditions; the fluctuation of the detection data is evaluated by analyzing the difference between the maximum value, the minimum value and the average value, where the fluctuation can be quantified by calculating the standard deviation or the coefficient of variation to reflect the stability of the detection data. Furthermore, the established data model is compared with the actual detection results to verify the accuracy of the model, and the model parameters of the data model are adjusted according to the verification results to improve the prediction ability and accuracy of the model.

[0070] For example, Figure 5 Schematic diagram of performance parameters of radar probe provided by exemplary embodiments of the present application. Figure 5 As shown, Figure 5 (a) reflects the detection area of ​​the radar probe and the stable feedback value of each area; Figure 5 (b) in the figure reflects the missed detection rate of each area of ​​the radar probe. The darker the color, the higher the missed detection rate. It can be seen that the missed detection rate at the edge of the detection field of view is relatively high. Figure 5(c) in the figure reflects the feedback value stability within the detection area of ​​the radar probe. The darker the color, the greater the value fluctuation. It can be observed that the value fluctuation at the edge of the detection field of view is more obvious.

[0071] The embodiments of the present application can more accurately reflect the steady-state characteristics of the detection data and reduce the impact of accidental errors by calculating the maximum, minimum and average values ​​of multiple distances corresponding to each obstacle coordinate. In addition, by establishing a data model that reflects the performance parameters of the radar probe, the performance parameters of the radar probe can be comprehensively reflected, providing data support for the comprehensive evaluation of the radar probe performance and the application of the radar probe.

[0072] In some embodiments, the data collection and processing method of the ultrasonic radar detection field of view also includes: controlling the radar probe to rotate a set angle along the center line of the radar probe to obtain performance parameters of the target model radar probe in the vertical range.

[0073] For example, multiple radar probes of target models are installed on a rotatable bracket to ensure that they can be accurately rotated along the center line. The rotatable bracket is deployed on the horizontal axis of the calibration cloth, and the obstacle is located at the calibration point of the calibration cloth; the radar probe is controlled to rotate along its center line to a set angle, such as 90 degrees, so that its detection field of view is switched from horizontal to vertical; when the radar probe is rotated to the vertical position, within a set time, such as T minutes, multiple radar probes are controlled in turn to periodically transmit signals to obtain the distance between the corresponding radar probe and the obstacle, where T can be, for example, 1, 5 or 10; based on the distance obtained when the obstacle is located at each calibration point , determine the third acquisition data set in the calibration coordinate system, further for each radar probe, take the radar probe as the origin, according to the coordinates of the radar probe, in the third acquisition data set, perform coordinate transformation on the obstacle coordinates mapped by the coordinates of the radar probe, and obtain the fourth acquisition data set in the radar probe coordinate system; for each obstacle coordinate in the fourth acquisition data set, determine the steady-state statistical information of multiple distances corresponding to the obstacle coordinate, and establish a target data model based on the steady-state statistical information corresponding to each obstacle coordinate in the fourth acquisition data set, the target data model reflects the performance parameters of the target model radar probe in the vertical range. For example, Figure 6 A schematic diagram of the detection area of ​​the radar probe in the vertical range and the stable feedback value of each area provided by the exemplary embodiment of the present application. Figure 5 (a) and Figure 6 , you can intuitively compare the target model's radar probe's detection area in the lateral and vertical ranges, as well as the stable feedback values ​​of each area.

[0074] In some embodiments, the method for collecting and processing data of the ultrasonic radar detection field of view further includes: obtaining horizontal comparison results of radar probes of different models based on data models corresponding to radar probes of different models.

[0075] For example, Figure 7 This is a schematic diagram comparing the performance parameters of the radar probe of target model 1 and the radar probe of target model 2 provided in the exemplary embodiment of the present application. Figure 7 As shown in the figure, through the data models corresponding to each type of radar probe, the performance of different types of radar probes can be compared horizontally in different dimensions, such as the actual detectable range and stable feedback value, missed detection rate, fluctuation of detection data, etc.

[0076] In the embodiments of the present application, through horizontal comparative analysis, the differences in key performance parameters of radar probes of different models can be obtained, which is convenient for identifying models with excellent and insufficient performance, and provides a basis for selecting appropriate radar probes; in addition, based on the horizontal comparison results, it is convenient to optimize the selection and configuration of radar probes to meet the needs of specific application scenarios, and provide data support for the design and development of radar systems.

[0077] In some embodiments, the method for collecting and processing data of the ultrasonic radar detection field of view further includes: determining a vehicle layout plan for a combination of multiple radar probes of the target model based on performance parameters of the radar probe of the target model.

[0078] For example, the performance parameters of the target model radar probe are obtained, including the detection range, missed detection rate, stable feedback value and fluctuation of the detection value; through these performance parameters, the detection capability of a single radar probe in different directions and distances is evaluated; based on the performance parameters of a single probe, a combination of multiple radar probes is designed to cover all key areas around the vehicle, and the installation position and orientation of each probe is determined to maximize the detection coverage and minimize the blind spot; the arrangement of multiple radar probes is simulated on the vehicle model to ensure that the detection areas between the radar probes have appropriate overlap to improve the overall detection accuracy and reliability, and the installation angle and orientation of the radar probes are optimized considering the shape and size of the vehicle. height to adapt to different driving environments and conditions; use simulation tools to simulate the multi-radar probe combination solution, verify its detection performance in various scenarios, and evaluate the effectiveness of the solution through detection coverage, blind spot size and detection accuracy; according to the simulation results, adjust the layout and combination strategy of radar probes, and further optimize the detection effect to ensure that the final solution can provide reliable detection capabilities in actual applications and meet the needs of vehicle safety and navigation; further apply the optimized multi-radar probe combination solution to actual vehicles and conduct field tests to verify the performance of the solution in real environments. During the verification process, field test data is collected simultaneously, and the solution is fine-tuned based on the field test data. For example, Figure 8 A schematic diagram of a vehicle layout scheme for multiple radar probe combinations provided by an exemplary embodiment of the present application. Figure 8As shown, by arranging a combination of multiple radar probes, key areas around the vehicle can be covered.

[0079] The embodiments of the present application, by utilizing the performance parameters of the target model radar probe, can effectively design and verify the combination of multiple radar probes, which not only improves the detection capability and safety of the vehicle, but also provides a solid foundation for the development of autonomous driving and advanced driver assistance systems.

[0080] In some embodiments, the method for collecting and processing data of the ultrasonic radar detection field of view further includes: determining a positional relationship between a target obstacle and a target vehicle based on a distance between the radar probe and the obstacle.

[0081] For example, an ultrasonic radar probe is installed on a target vehicle to ensure that it covers key areas around the vehicle; the radar probe is started to collect distance data of obstacles around the vehicle, the distance data including the distance information between each obstacle and the radar probe; based on the installation position of the radar probe and the coordinate system of the vehicle, the distance data of each obstacle is converted into position coordinates in the vehicle coordinate system; the relative position of the obstacle in the vehicle coordinate system is calculated, including the lateral and longitudinal distances; based on the converted coordinates, the positional relationship between the target obstacle and the target vehicle is determined, the specific position of the obstacle around the vehicle (e.g., front, rear, left or right) is identified, and its relative distance and angle to the vehicle are calculated.

[0082] In some embodiments, the data collection and processing method of the ultrasonic radar detection field of view also includes: establishing a dynamic position relationship between the target obstacle and the target vehicle based on the distance between the radar probe and the obstacle, and simulating to obtain the real-time distance between the radar probe and the obstacle corresponding to different position relationships.

[0083] For example, a radar probe is installed on the target vehicle to ensure that it can cover the key areas around the vehicle; the radar probe is started to collect distance data of obstacles in real time, wherein the distance data includes the distance between each obstacle and the radar probe; the collected distance data is combined with the motion state of the vehicle (such as speed and direction) to establish a dynamic position relationship between the obstacle and the vehicle; the coordinate transformation technology is used to transform the distance data of the obstacle into dynamic position coordinates in the vehicle coordinate system, and its relative position and motion trajectory are calculated; in the simulation environment, different vehicle and obstacle position relationship scenarios are set to simulate the movement of the vehicle at different speeds and directions, as well as the dynamic changes of obstacles.

[0084] Accordingly, in a simulation environment, simulation tools can also be used to simulate the detection process of the radar probe and record real-time distance data under different position relationships; analyze the real-time distance data obtained by simulation to verify the accuracy of the dynamic position relationship model, such as by comparing the simulation data with the actual collected data to evaluate the reliability and applicability of the model; optimize the configuration of the dynamic position relationship model and the radar probe according to the simulation results, such as adjusting the data processing algorithm to improve the accuracy and response speed of real-time distance calculation; further, apply the optimized model to actual vehicles for field testing to verify its performance in a real driving environment, collect field test data during the verification process, and further optimize and adjust the model and method based on the field test data to ensure that it provides reliable dynamic position relationships and real-time distance information in actual applications.

[0085] The embodiments of the present application provide important data support for autonomous driving and advanced driver assistance systems by establishing and verifying the dynamic position relationship between the target obstacle and the target vehicle and obtaining real-time distance data under different position relationships in a simulation environment, thereby improving the safety and reliability of the entire vehicle system.

[0086] Fig. 9 Another flow chart of the method for collecting and processing data of ultrasonic radar detection field of view provided by the exemplary embodiment of the present application. Fig. 9 As shown, the data collection and processing method of the ultrasonic radar detection field of view includes the following steps:

[0087] S901. Within a set time period, control multiple radar probes to periodically transmit signals in sequence to obtain the distance between the corresponding radar probe and the obstacle. The radar probes are deployed on the horizontal axis of the calibration cloth, and the obstacle is located at the calibration point of the calibration cloth.

[0088] The calibration points are the endpoints of the grids in the calibration cloth; the width of each grid in the calibration cloth is the set length, and the remainders of the distances between different radar probes and the origin of the calibration cloth divided by the set length are different.

[0089] For example, when the obstacle is located at the calibration point (X1, Y1), within a set time period, such as T minutes, multiple radar probes are sequentially controlled to transmit signals at set time intervals, where T can be, for example, 1, 5, or 10, and the time interval can be, for example, 50ms or 100ms; Figure 3 As shown, when the coordinates of the obstacle are (X1, Y1), the distances between each radar probe and the obstacle are obtained, for example, La1, Lb1, Lc1 and Ld1, respectively, where La1, Lb1, Lc1 and Ld1 represent a set of distance values. Further, the obstacle is moved to the next calibration point of the calibration cloth, and the distances between each radar probe and the obstacle are obtained again. After traversing all the calibration points on the calibration cloth, the data collection work is completed.

[0090] S902: Determine a first acquisition data set in a calibration coordinate system, where the first acquisition data set includes a mapping relationship between obstacle coordinates, radar probe coordinates, and distances.

[0091] S903: Determine whether there are target obstacle coordinates that are not grid endpoint coordinates in the obstacle coordinates.

[0092] If yes, execute S904;

[0093] If not, execute S905.

[0094] S904: Delete the target obstacle coordinates and the distances that are mapped to the target obstacle coordinates in the first acquired data set.

[0095] For example, if there are target obstacle coordinates such as (X2, Y2), then in the first acquired data set, the target obstacle coordinates (X2, Y2) and the distances La2, Lb2, Lc2 and Ld2 that are mapped to (X2, Y2) are deleted.

[0096] S905. For each radar probe, take the radar probe as the origin, and perform coordinate transformation on the obstacle coordinates mapped by the coordinates of the radar probe in the first acquisition data set according to the coordinates of the radar probe to obtain a second acquisition data set in the radar probe coordinate system.

[0097] S906. For each obstacle coordinate in the second acquired data set, determine steady-state statistical information of multiple distances corresponding to the obstacle coordinate, where the steady-state statistical information includes a maximum value, a minimum value, and an average value of the multiple distances.

[0098] S907: Establish a data model based on the steady-state statistical information corresponding to the coordinates of each obstacle in the second acquired data set, where the data model reflects the performance parameters of the radar probe of the target model.

[0099] Among them, the performance parameters include the probe missed detection rate, the actual detectable range, the stable feedback value and the fluctuation of the detection data.

[0100] S908. Determine a vehicle layout plan for a combination of multiple radar probes of the target model based on performance parameters of the radar probe of the target model.

[0101] For example, Figure 8 As shown, through the combined arrangement of multiple radar probes, the key areas around the vehicle can be covered.

[0102] In summary, this application has at least the following advantages:

[0103] First, by automatically controlling multiple radar probes to work together and converting the data sets collected in the calibration coordinate system corresponding to the multiple radar probes into the data sets collected in the radar probe coordinate system, the detection data of multiple radar probes can be obtained simultaneously in one data collection, which significantly improves the efficiency of data collection compared to the traditional method of measuring one radar probe at a time. In addition, by automatically controlling multiple radar probes, manual intervention is reduced, human errors in the data collection process are reduced, and the accuracy of the data is improved.

[0104] Second, by ensuring that the remainders of the distances between different radar probes and the origin of the calibration cloth divided by the set length are different, the position of the obstacle can be located more accurately, thereby achieving more fine-grained coordinate positioning.

[0105] 3. By periodically transmitting signals within a set time, a set of stable detection data can be obtained, reducing the accidental errors that may be caused by a single acquisition and improving the reliability of the collected data; in addition, by obtaining stable detection data, the robustness and reliability in the face of complex environments and changing conditions can be improved.

[0106] 4. By collecting data and establishing a data model that reflects the performance parameters of radar probes, the performance of different types of radar probes can be more objectively quantified and finely compared, which is convenient for radar selection and adaptation of application functions. The data model based on radar probes can be expanded to multi-radar coordination to achieve vehicle-level radar function estimation and simulation, and further can realize simulation during motion, which can provide important data support for autonomous driving and advanced driver assistance systems, thereby improving the safety and reliability of the vehicle system.

[0107] Fig.10 A schematic diagram of a data acquisition and processing device for ultrasonic radar detection field of view provided by an exemplary embodiment of the present application. Fig.10 As shown, the data acquisition and processing device 100 of the ultrasonic radar detection field of view includes a control module 101, a determination module 102 and a processing module 103, wherein:

[0108] The control module 101 is used to control multiple radar probes to transmit signals in sequence to obtain the distance between the corresponding radar probe and the obstacle, the radar probes are deployed on the horizontal axis of the calibration cloth, and the obstacle is located at the calibration point of the calibration cloth;

[0109] A determination module 102 is used to determine a first acquisition data set in a calibration coordinate system based on the distance obtained when the obstacle is located at each calibration point, where the first acquisition data set includes a mapping relationship between the obstacle coordinates, the radar probe coordinates, and the distance;

[0110] The processing module 103 is used to transform the obstacle coordinates mapped by the coordinates of the radar probe in the first acquisition data set according to the coordinates of the radar probe for each radar probe, taking the radar probe as the origin, to obtain a second acquisition data set in the radar probe coordinate system.

[0111] In a possible implementation, the width of each grid in the calibration cloth is a set length, and the remainders of the distances between different radar probes and the origin of the calibration cloth divided by the set length are different.

[0112] In one possible implementation, the calibration point is a grid endpoint in the calibration cloth. Before the obstacle coordinates mapped by the coordinates of the radar probe are converted, the processing module 103 can be specifically used to: determine whether there are target obstacle coordinates that are not grid endpoint coordinates in the obstacle coordinates of the obstacle; if there are target obstacle coordinates, then in the first acquisition data set, delete the target obstacle coordinates and the distance that has a mapping relationship with the target obstacle coordinates.

[0113] In a possible implementation, the multiple radar probes are target-type radar probes, and the control module 101 may be specifically used to control the multiple radar probes to periodically transmit signals in sequence within a set time period.

[0114] In a possible implementation, the processing module 103 can also be used to: determine, for each obstacle coordinate in the second acquisition data set, steady-state statistical information of multiple distances corresponding to the obstacle coordinates, the steady-state statistical information including the maximum value, minimum value and average value of the multiple distances; establish a data model based on the steady-state statistical information corresponding to each obstacle coordinate in the second acquisition data set, the data model reflecting the performance parameters of the radar probe of the target model, the performance parameters including the probe missed detection rate, the actual detectable range, the stable feedback value and the fluctuation of the detection data.

[0115] In a possible implementation, the processing module 103 can also be used to: control the radar probe to rotate to a set angle along the center line of the radar probe to obtain performance parameters of the target model's radar probe in the vertical range; obtain lateral comparison results of radar probes of different models based on data models corresponding to radar probes of different models; and determine a vehicle layout plan for a combination of multiple radar probes of the target model based on the performance parameters of the radar probe of the target model.

[0116] In a possible implementation, the processing module 103 may also be used to: determine the positional relationship between the target obstacle and the target vehicle based on the distance between the radar probe and the obstacle; and / or, establish a dynamic positional relationship between the target obstacle and the target vehicle based on the distance between the radar probe and the obstacle, and simulate and obtain the real-time distance between the radar probe and the obstacle corresponding to different positional relationships.

[0117] The data acquisition and processing device for the ultrasonic radar detection field of view provided in the embodiment of the present application can execute the technical solution shown in the above-mentioned data acquisition and processing method embodiment of the ultrasonic radar detection field of view. Its implementation principle and beneficial effects are similar and will not be repeated here.

[0118] It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. And these modules can all be implemented in the form of software called by processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware. For example, the processing module can be a separately established processing element, or it can be integrated in a chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and called and executed by a processing element of the above device. The implementation of other modules is similar. In addition, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module above can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

[0119] For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASIC), or one or more microprocessors (DSP), or one or more field programmable gate arrays (FPGA). For another example, when a module is implemented in the form of a processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0120] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loading and executing computer instructions on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (Digital Subscriber Line, referred to as DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, a data center, etc. that contains one or more available media integrated. Available media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, Digital Video Discs (DVDs)), or semiconductor media (eg, solid state disks (SSDs)).

[0121] Fig.11 The schematic diagram of the structure of the electronic device provided by the exemplary embodiment of the present application. Fig.11 As shown, the electronic device 110 of this embodiment includes:

[0122] At least one processor 111; and a memory 112 communicatively connected to the at least one processor;

[0123] The memory 112 stores instructions that can be executed by the at least one processor 111, and the instructions are executed by the at least one processor 111 to enable the electronic device to execute the method described in any of the above embodiments.

[0124] Optionally, the memory 112 may be independent or integrated with the processor 111 .

[0125] The memory 112 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0126] The processor 111 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. Specifically, when implementing the data collection and processing method of the ultrasonic radar detection field of view described in the aforementioned method embodiment, the electronic device may be, for example, an electronic device with processing function such as a server.

[0127] Optionally, the electronic device may further include a communication interface 113. In a specific implementation, if the communication interface 113, the memory 112 and the processor 111 are implemented independently, the communication interface 113, the memory 112 and the processor 111 may be interconnected through a bus and communicate with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc., but it does not mean that there is only one bus or one type of bus.

[0128] Optionally, in a specific implementation, if the communication interface 113, the memory 112 and the processor 111 are integrated on a chip, the communication interface 113, the memory 112 and the processor 111 can communicate through an internal interface.

[0129] The implementation principle and technical effects of the electronic device provided in this embodiment can be found in the aforementioned embodiments and will not be described in detail here.

[0130] An embodiment of the present application also provides a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed, they are used to implement the method steps in the above method embodiment. The specific implementation method and technical effect are similar and will not be repeated here.

[0131] The above-mentioned computer readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable programmable read only memory (EPROM), programmable read only memory (PROM), read only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0132] An exemplary readable storage medium is coupled to the processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in a dedicated integrated circuit. Of course, the processor and the readable storage medium can also exist as discrete components in the data acquisition and processing device of the ultrasonic radar detection field of view.

[0133] The embodiment of the present application also provides a computer program product, including a computer program. When the computer program is executed, the method steps in the above method embodiment are implemented. The specific implementation method and technical effect are similar and will not be repeated here.

[0134] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0135] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for collecting and processing data of ultrasonic radar detection field of view, characterized in that: include: Controlling multiple radar probes to transmit signals in sequence to obtain the distance between the corresponding radar probes and obstacles, wherein the radar probes are deployed on the horizontal axis of a calibration cloth, and the obstacles are located at calibration points of the calibration cloth; Based on the distances obtained when the obstacle is located at each calibration point, determining a first acquisition data set in a calibration coordinate system, wherein the first acquisition data set includes a mapping relationship between the obstacle coordinates, the coordinates of the radar probe, and the distances; For each radar probe, the radar probe is taken as the origin, and according to the coordinates of the radar probe, in the first acquisition data set, the coordinates of the obstacle mapped by the coordinates of the radar probe are transformed to obtain a second acquisition data set in the radar probe coordinate system.

2. The method according to claim 1, characterized in that The width of each grid in the calibration cloth is a set length, and the remainders of the distances between different radar probes and the origin of the calibration cloth divided by the set length are different.

3. The method according to claim 1 or 2, characterized in that: The calibration points are grid endpoints in the calibration cloth, and before the coordinate transformation of the obstacle coordinates mapped to the radar probe is performed, the method further includes: Determine whether there is a target obstacle coordinate that is not a grid endpoint coordinate among the obstacle coordinates of the obstacle; If the target obstacle coordinates exist, the target obstacle coordinates and the distance having a mapping relationship with the target obstacle coordinates are deleted from the first acquired data set.

4. The method according to claim 1 or 2, characterized in that: The multiple radar probes are radar probes of target models, and sequentially controlling the multiple radar probes to transmit signals includes: Within a set time period, the multiple radar probes are controlled in sequence to periodically transmit signals.

5. The method according to claim 4, characterized in that Also includes: For each obstacle coordinate in the second acquired data set, determine steady-state statistical information of multiple distances corresponding to the obstacle coordinate, the steady-state statistical information including a maximum value, a minimum value, and an average value of the multiple distances; Based on the steady-state statistical information corresponding to the coordinates of each obstacle in the second acquired data set, a data model is established, wherein the data model reflects the performance parameters of the radar probe of the target model, and the performance parameters include the probe missed detection rate, the actual detectable range, the stable feedback value and the fluctuation of the detection data.

6. The method according to claim 5, characterized in that Also includes at least one of the following: Control the radar probe to rotate along the center line of the radar probe by a set angle to obtain performance parameters of the radar probe of the target model in a vertical range; Based on the data models corresponding to different types of radar probes, the horizontal comparison results of different types of radar probes are obtained; Based on the performance parameters of the radar probe of the target model, a vehicle layout scheme of a combination of multiple radar probes of the target model is determined.

7. The method according to claim 5, characterized in that Also includes: Determining the positional relationship between the target obstacle and the target vehicle based on the distance between the radar probe and the obstacle; And / or, based on the distance between the radar probe and the obstacle, a dynamic position relationship between the target obstacle and the target vehicle is established, and the real-time distance between the radar probe and the obstacle corresponding to different position relationships is obtained by simulation.

8. A data acquisition and processing device for ultrasonic radar detection field of view, characterized in that: include: A control module, used for sequentially controlling a plurality of radar probes to transmit signals to obtain the distance between the corresponding radar probes and obstacles, wherein the radar probes are deployed on the horizontal axis of a calibration cloth, and the obstacles are located at calibration points of the calibration cloth; A determination module, configured to determine a first acquisition data set in a calibration coordinate system based on the distance obtained when the obstacle is located at each calibration point, wherein the first acquisition data set includes a mapping relationship between the obstacle coordinates, the coordinates of the radar probe, and the distance; The processing module is used to transform the coordinates of obstacles mapped by the coordinates of the radar probe in the first acquisition data set according to the coordinates of the radar probe for each radar probe, taking the radar probe as the origin, to obtain a second acquisition data set in the radar probe coordinate system.

9. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory is used to store computer-executable instructions; The processor is used to execute the computer-executable instructions to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed.

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