Radar positioning track and target true value track matching method, system, device and medium

Abstract

The application relates to the technical field of data processing, and discloses a radar positioning track and target true value track matching method, system, device and medium, the method comprising the following steps: preprocessing radar positioning track data and true value track data to obtain standardized track data; initializing matching parameters, setting a space screening window threshold and a track matching degree threshold; sequentially performing invalid value elimination, space coarse screening and time coarse screening on the standardized track data by using the matching parameters to obtain effective track data after coarse screening; performing piece-by-piece comparison and point-by-point matching on the effective track data based on the matching parameters; and calculating the ratio of the number of matched points to the total number of points in the radar positioning track and the true value track to obtain a matching degree, when the matching degree is not less than a set threshold, associating the batch numbers of the corresponding radar positioning track and the true value track, completing track matching and obtaining matched track data. The application improves the speed of track matching and the reliability of the matching result.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, system, device and medium for matching radar positioning tracks with target true tracks. Background Technology

[0002] Radars accumulate a vast amount of target location track data during routine operation. Open-source websites and data companies also possess a wealth of open-source data, such as ADS-B, AIS, and GPS, which can be used for matching and selection. Systematic radar calibration utilizes the positioning data generated during routine radar operation and the open-source target ground truth data (ADS-B, AIS, GPS, etc.) to calibrate and continuously maintain radar positioning performance. The key to systematic radar calibration technology is selecting effective calibration data for error analysis from the large amount of radar positioning track data and target ground truth track data.

[0003] Traditional track matching methods mainly include rectangular box filtering based on fixed spatiotemporal thresholds, nearest neighbor distance association, and track clustering algorithms. While these methods can achieve basic track association, they all have significant limitations. Fixed threshold methods rely heavily on manually preset parameters such as the size of the spatiotemporal window, resulting in poor generalization ability when facing different radars or complex scenarios, requiring repeated parameter tuning. Nearest neighbor methods are prone to mismatches when targets are dense or tracks intersect, as they rely solely on spatial proximity. They also have weak anti-interference capabilities. While high-precision algorithms (such as DTW) can improve accuracy, their huge computational cost makes it difficult to meet the needs of real-time processing of massive historical data.

[0004] In summary, existing methods struggle to balance adaptability, robustness, and efficiency, hindering the automation, efficiency, and large-scale application of radar system calibration processes. Summary of the Invention

[0005] In view of this, this application provides a method, system, device and medium for matching radar positioning tracks with target true tracks, which can adapt to changes in environment and equipment and has a lightweight design to achieve a new type of track matching with high efficiency, thereby improving the speed of track matching and the reliability of matching results.

[0006] This application discloses a method for matching radar positioning tracks with target ground truth tracks, which includes: Step 1: Preprocess the radar positioning track data and ground truth track data, extract relevant parameters, and convert the relevant parameters into a unified standard format to obtain standardized track data; the relevant parameters include timestamp, longitude, latitude, altitude, and batch number; Step 2: Initialize the matching parameters, and set the spatial filtering window threshold and track matching degree threshold; Step 3: Use matching parameters to sequentially remove invalid values, perform spatial coarse filtering, and temporal coarse filtering on the standardized track data to obtain the coarsely filtered valid track data; Step 4: Based on the matching parameters, perform line-by-line comparison and point-by-point matching of valid track data. Point matching is completed by judging the time, longitude, latitude, and altitude window thresholds. The ratio of the number of successfully matched points in the radar positioning track and the true value track to the total number of points is calculated to obtain the matching degree. When the matching degree is not less than the set threshold, the batch number of the corresponding radar positioning track and the true value track is associated to complete the track matching and obtain the matched track data.

[0007] Further, step 1 includes: Extract timestamps, latitude, longitude, altitude, and batch number from radar positioning track data; extract timestamps, latitude, longitude, altitude, and batch number from ground truth track data; sort the extracted data by batch number, and then sort the data within a single batch by timestamp to obtain standardized track data.

[0008] Further, step 2 includes: Step 21: Obtain the radar's maximum detection range As a spatial coarse screening threshold, and to obtain the longitude of radar deployment. ,latitude ,high ; Step 22: Set the spatial filtering window thresholds for longitude, latitude, and altitude. , , and track matching threshold Complete the initialization of matching parameters.

[0009] Further, step 3 includes: Step 31: Remove invalid data containing null values ​​or NAN, and remove abnormal data with longitude exceeding ±180°, latitude exceeding ±90°, altitude ≤0, or timestamps that are not positive. Step 32: Based on the latitude and longitude coordinates of the radar deployment and the maximum detection range of the radar The target spatial range is calculated using the following formula:

[0010]

[0011]

[0012]

[0013] in, , These are the minimum and maximum latitudes for spatial filtering, respectively. , These are the minimum and maximum longitudes for spatial filtering, respectively. This represents the radar's maximum detection range. Remove true track data that is not within the target space range; Step 33: Extract the time interval of radar positioning track and the time interval of the true value track , For the smallest timestamp, For the maximum timestamp, For the smallest timestamp, Use the maximum timestamp; remove tracks that are not present in the true value track. Data within; excluding data not present in radar positioning tracks. The data within the data set is then used to perform a coarse screening of radar positioning tracks and true track data, achieving overall alignment of the data distribution in time and space.

[0014] Further, step 4 includes: Step 41: Read radar positioning track data by batch number, and retain only valid tracks with a track point count greater than the preset number; read true track data according to the same rules, and retain only valid tracks with a track point count greater than the preset number. Step 42: Using the radar positioning track point as a reference, match it point by point with the true value track point; let the coordinates of the radar positioning track point be... The true track point coordinates are Two-point matching must satisfy the following formula:

[0015]

[0016]

[0017] in, , , These are the longitude, latitude, and altitude of the radar positioning track point, respectively. , , These are the true value longitude, latitude, and altitude of the waypoint; For east-west speed, For north-south speed, Vertical velocity, These are the filtering threshold windows for longitude, latitude, and altitude, respectively.

[0018]

[0019]

[0020]

[0021] in, The time reference error between the two tracks The difference between the timestamps of the two points. The waypoint number; Step 43: Count the total number of radar positioning track points. Points of successful match The matching degree between the radar-positioned track and the true track is calculated using the following formula:

[0022] When the matching degree At that time, it is determined that the radar positioning track and the true track are successfully matched; Step 44: Associate the successfully matched radar positioning track batch number with the true value track batch number, and store the corresponding track points in the valid database; Step 45: Traverse all radar positioning track data by batch number, repeat steps 41 to 44, and complete all track matching.

[0023] Furthermore, after step 4, the method further includes: Step 5: Using the matched track data, adaptively extract and optimize the filtering window threshold and matching degree threshold to obtain the optimized matching parameters.

[0024] Further, step 5 includes: Step 51: Select a set of matched and associated radar positioning track data and ground truth track data as parameter optimization samples; Step 52: Using the parameter optimization sample as input data, perform the matching calculations from Step 2 to Step 4. Adjust the size of the filtering window according to the value of the matching degree P obtained in real time, and use the corresponding filtering window threshold as the optimized matching parameter.

[0025] This application also discloses a radar positioning track and target true track matching system, which implements the above-described method and includes: The preprocessing module is used to preprocess radar positioning track data and ground truth track data, extract relevant parameters, and convert the relevant parameters into a unified standard format to obtain standardized track data; the relevant parameters include timestamp, longitude, latitude, altitude, and batch number; The parameter initialization module is used to initialize the matching parameters and set the spatial filtering window threshold and track matching degree threshold. The coarse screening module is used to perform invalid value removal, spatial coarse screening, and temporal coarse screening on the standardized track data in sequence using matching parameters to obtain the coarsely screened valid track data. The track matching module is used to compare and match valid track data line by line and point by point based on matching parameters. Point matching is completed by judging the time, longitude, latitude, and altitude window thresholds. The matching degree is obtained by calculating the ratio of the number of successfully matched points in the radar positioning track and the true value track to the total number of points. When the matching degree is not less than the set threshold, the batch number of the corresponding radar positioning track and the true value track is associated to complete the track matching and obtain the matched track data.

[0026] This application also discloses an electronic device, including a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, implements the method described in any of the above-described embodiments.

[0027] This application also discloses a computer-readable storage medium comprising a computer program or instructions that, when executed on a computer, cause the computer to perform any of the methods described above.

[0028] Due to the adoption of the above technical solution, this application has the following advantages: 1. The trajectory matching method based on the spatiotemporal correlation characteristics of this application directly performs time and space window filtering on latitude and longitude high positioning trajectory data. It is simple and direct, without the need for coordinate transformation and complex data value calculation. In addition, the matching of each trajectory is independent of each other, naturally supporting parallel computing and supporting the need for rapid processing of large amounts of trajectory data. 2. This application introduces a method for calculating track matching degree and a matching judgment principle. This method has good robustness and generalization ability in terms of matching success rate. From the perspective of engineering practice, the two sets of matching parameters can be adapted to most maritime radars and air radars, and can support the automation and large-scale application of the algorithm. 3. This application automates the setting of matching parameters by using an adaptive matching parameter extraction method, thereby automating the entire data matching and filtering process. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in the embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings.

[0030] Figure 1 This is a flowchart illustrating a method for matching radar positioning tracks with target true tracks according to an embodiment of this application. Figure 2 This is a flowchart illustrating another method for matching radar positioning tracks with target true tracks according to an embodiment of this application. Figure 3 This is a logic diagram of the adaptive matching parameter extraction method according to an embodiment of this application. Detailed Implementation

[0031] The present application will be further described in conjunction with the accompanying drawings and embodiments. The described embodiments are only some, not all, of the embodiments of the present application. All other embodiments obtained by those skilled in the art should fall within the protection scope of the embodiments of the present application.

[0032] To quickly select effective data matching pairs from a large amount of radar positioning track data and target ground truth data such as ADS-B / AIS / GPS to support the analysis of radar positioning error characteristics, see [reference needed]. Figures 1 to 3 This application provides an embodiment of a method for matching radar positioning tracks with target true tracks. In this embodiment, the radar is an air search radar, and the true track data is civil aviation ADS-B data. The specific steps include: Step 1: Preprocess the radar positioning track data and ground truth track data, extract relevant parameters, and convert the relevant parameters into a unified standard format to obtain standardized track data; the relevant parameters include timestamp, longitude, latitude, altitude, and batch number; Step 2: Initialize the matching parameters, and set the spatial filtering window threshold and track matching degree threshold; Step 3: Use matching parameters to sequentially remove invalid values, perform spatial coarse filtering, and temporal coarse filtering on the standardized track data to obtain the coarsely filtered valid track data; Step 4: Based on the matching parameters, perform line-by-line comparison and point-by-point matching of valid track data. Point matching is completed by judging the time, longitude, latitude, and altitude window thresholds. The ratio of the number of successfully matched points in the radar positioning track and the true value track to the total number of points is calculated to obtain the matching degree. When the matching degree is not less than the set threshold, the batch number of the corresponding radar positioning track and the true value track is associated to complete the track matching and obtain the matched track data.

[0033] In step 1, fields such as timestamp, longitude, latitude, altitude, and batch number that can be used for matching analysis are extracted from radar positioning track and ground truth track data, and converted into a unified standard format. The specific implementation method includes the following steps: Step 1.1: Extract the timestamp, longitude, latitude, altitude, and batch number fields from the radar positioning track data. The timestamp uses a Unix timestamp with millisecond precision; latitude and longitude are in decimal format, retaining 6 decimal places, with positive and negative signs indicating hemispheres; altitude is in meters, retaining 2 decimal places; the batch number uses the track batch number in pure numerical format. If the original batch number is a string, it needs to be converted to a number.

[0034] The standard format of radar data and the corresponding extracted fields are shown in Table 1: Table 1. Radar Data Standard Format Correspondence Table

[0035] Step 1.2: Extract timestamp, longitude, latitude, altitude, and batch number fields from the ground truth flight track data. The timestamp uses a Unix timestamp with millisecond precision; latitude and longitude are in decimal format, retaining 6 decimal places, with positive and negative signs indicating hemispheres; altitude is in meters, retaining 2 decimal places; the batch number is based on the flight number from the data source, in pure numeric format, and the original batch number (if it was a string, it needs to be converted to a number).

[0036] The ADS-B data standard format and corresponding extracted fields are shown in Table 2: Table 2. ADS-B Data Standard Format Correspondence Table

[0037] Step 1.3: Sort the extracted data by batch number first, and then sort the data within a single batch by time.

[0038] In step 2, the matching parameters are initialized, including the initialization settings of the filter window threshold and the matching degree threshold. The specific implementation method includes the following steps: Step 2.1: Review the radar design parameters to obtain the equipment's maximum detection range. As a threshold for coarse filtering of the data space, the equipment manual was consulted to obtain the radar's deployment latitude, longitude, and altitude coordinates. In this embodiment, the specific parameter settings are shown in Table 3: Table 3 Coarse Screening Parameter Settings

[0039] Step 2.2: Set up the space filtering window based on engineering experience. Matching threshold In this embodiment, the data set are all parameters optimized in step 5, as shown in Table 4.

[0040] Table 4 Matching Parameter Settings

[0041] In step 3, the track data undergoes coarse screening, which involves removing invalid values, performing temporal coarse screening, and spatial coarse screening on the standardized data. This efficiently removes most of the invalid data, reducing the workload of subsequent matching analysis. The specific implementation method includes the following steps: Step 3.1, remove invalid values. First, remove data with missing field values, such as null values ​​or NAN values. Second, remove data values ​​that are outside the range of the specified range: longitude values ​​are within ±180°, latitude values ​​are within ±90°, altitude values ​​are greater than 0, and timestamps are positive.

[0042] Step 3.2, spatial coarse screening, firstly using the latitude and longitude coordinates of radar deployment. and the equipment's maximum detection range The approximate spatial range in which the radar-located target may appear is calculated, as shown below.

[0043]

[0044]

[0045]

[0046] in Minimum latitude value, The maximum latitude value, The minimum longitude value, The maximum longitude value is used, and then true value track data that is not in this area is removed.

[0047] Step 3.3, coarse time filtering: First, calculate the minimum timestamp of the radar positioning track distribution using timestamps. Maximum timestamp Then calculate the minimum timestamp of the true track data distribution. Maximum timestamp Next, remove true track data that is not within the time interval. Within the data range, remove true value track data that are not within the time interval. The data within the data set is then used to perform a coarse screening of radar positioning tracks and true track data, achieving overall alignment of the data distribution in time and space.

[0048] In step 4, track matching is performed. After the initial overall data screening, radar positioning track data is extracted from the coarsely screened data and compared with the ground truth track data line by line. First, track points are filtered and matched point by point. Threshold judgments are made by setting time, longitude, latitude, and altitude windows to complete the filtering. Then, the ratio of successfully matched points in each track pair to the total number of points is calculated to determine the matching degree of the positioning track and the ground truth track. When the matching degree reaches the set threshold, the data batch numbers of the positioning track and the ground truth track are associated, thus completing the matching of a track. The specific implementation method includes the following steps: Step 4.1, matching data reading: Read a complete track data from the radar positioning track data according to the batch number. If the number of track points is greater than 10, continue to the next step; otherwise, the data is invalid and a new data is read and re-evaluated. Then, read a track data from the true value track data. If the number of track points is greater than 10, continue to the next step; otherwise, the data is invalid and a new data is read and re-evaluated.

[0049] Step 4.2, track point matching: The read radar positioning track data is matched point by point with the ground truth track data. Using the radar positioning track point as a reference, it is determined whether a ground truth track point is found to match it. The method for determining whether two track points match and are associated is as follows: Assume the latitude, longitude, and altitude coordinates of the radar positioning track point are: The true track point coordinates are For two points to be matched and associated, the following equation must be satisfied:

[0050]

[0051]

[0052] in, , , These are the longitude, latitude, and altitude of the radar positioning track point, respectively. , , These are the true value longitude, latitude, and altitude of the waypoint; The east-west speed (degrees per second) The north-south speed (degrees per second) Vertical velocity (degrees per second). These are the filtering threshold windows for longitude, latitude, and altitude, respectively.

[0053]

[0054]

[0055]

[0056]

[0057] in, The time reference error between the two tracks (in this embodiment, we take...) ), The difference between the timestamps of the two points. This refers to the waypoint number.

[0058] Step 4.3: Track matching. Then, calculate the ratio of successfully matched points in each track pair to the total number of points, and determine the positioning track matching degree and the true track matching degree. Count the total number of radar positioning track points. The number of successfully matched points is Then the matching degree The following formula can be used for calculation:

[0059] For two tracks to be matched and associated, the following conditions must be met. .

[0060] Step 4.4: Match track data storage, associate the matched radar positioning track batch number with the true value track batch number, and store all radar positioning tracks and true value track points under that batch number into the valid database.

[0061] Step 4.5: Complete the matching of all data. Repeat steps 4.1 to 4.4, reading track data from the radar positioning track data batch by batch and matching it with the true track data. Continue this process, reading each track data from the true track data and matching it, until a match is found or all the true track data has been traversed. In this embodiment, from over 1 million data points, over 50,000 valid data points were selected through matching.

[0062] Optionally, after step 4, the following steps are also included: Step 5: Using the matched track data, adaptively extract and optimize the filtering window threshold and matching degree threshold to obtain the optimized matching parameters.

[0063] Optionally, step 5 includes: Step 51: Select a set of matched and associated radar positioning track data and ground truth track data as parameter optimization samples; Step 52: Using the parameter optimization sample as input data, perform the matching calculations from Step 2 to Step 4. Adjust the size of the filtering window according to the value of the matching degree P obtained in real time, and use the corresponding filtering window threshold as the optimized matching parameter.

[0064] Optionally, if the matching degree P calculated in step 4 is less than 50%, the spatial filtering window threshold in step 2 is adjusted to increase the spatial filtering window. If the matching degree P is greater than 50%, the spatial filtering window is decreased until P is approximately equal to 50%. At this point, the spatial filtering window is the optimized matching parameter.

[0065] In this embodiment, two selected flight track data are used for parameter optimization and extraction. Step 5 is executed, and the optimized parameters are shown in the matching parameter setting table in step 2.

[0066] This application provides an embodiment of a method for matching radar positioning tracks with target true tracks, comprising: Step 1: Preprocess the radar positioning track data and ground truth track data, extract relevant parameters, and convert the relevant parameters into a unified standard format to obtain standardized track data; the relevant parameters include timestamp, longitude, latitude, altitude, and batch number; Step 2: Initialize the matching parameters, and set the spatial filtering window threshold and track matching degree threshold; Step 3: Use matching parameters to sequentially remove invalid values, perform spatial coarse filtering, and temporal coarse filtering on the standardized track data to obtain the coarsely filtered valid track data; Step 4: Based on the matching parameters, perform line-by-line comparison and point-by-point matching of valid track data. Point matching is completed by judging the time, longitude, latitude, and altitude window thresholds. The ratio of the number of successfully matched points in the radar positioning track and the true value track to the total number of points is calculated to obtain the matching degree. When the matching degree is not less than the set threshold, the batch number of the corresponding radar positioning track and the true value track is associated to complete the track matching and obtain the matched track data.

[0067] Optionally, step 1 includes: Extract timestamps, latitude, longitude, altitude, and batch number from radar positioning track data; extract timestamps, latitude, longitude, altitude, and batch number from ground truth track data; sort the extracted data by batch number, and then sort the data within a single batch by timestamp to obtain standardized track data.

[0068] Optionally, step 2 includes: Step 21: Obtain the radar's maximum detection range As a spatial coarse screening threshold, and to obtain the longitude of radar deployment. ,latitude ,high ; Step 22: Set the spatial filtering window thresholds for longitude, latitude, and altitude. , , and track matching threshold Complete the initialization of matching parameters.

[0069] Optionally, step 3 includes: Step 31: Remove invalid data containing null values ​​or NAN, and remove abnormal data with longitude exceeding ±180°, latitude exceeding ±90°, altitude ≤0, or timestamps that are not positive. Step 32: Based on the latitude and longitude coordinates of the radar deployment and the maximum detection range of the radar The target spatial range is calculated using the following formula:

[0070]

[0071]

[0072]

[0073] in, , These are the minimum and maximum latitudes for spatial filtering, respectively. , These are the minimum and maximum longitudes for spatial filtering, respectively. This represents the radar's maximum detection range. Remove true track data that is not within the target space range; Step 33: Extract the time interval of radar positioning track and the time interval of the true value track , For the smallest timestamp, For the maximum timestamp, For the smallest timestamp, Use the maximum timestamp; remove tracks that are not present in the true value track. Data within; excluding data not present in radar positioning tracks. The data within the data set is then used to perform a coarse screening of radar positioning tracks and true track data, achieving overall alignment of the data distribution in time and space.

[0074] Optionally, step 4 includes: Step 41: Read radar positioning track data by batch number, and retain only valid tracks with a track point count greater than the preset number; read true track data according to the same rules, and retain only valid tracks with a track point count greater than the preset number. Step 42: Using the radar positioning track point as a reference, match it point by point with the true value track point; let the coordinates of the radar positioning track point be... The true track point coordinates are Two-point matching must satisfy the following formula:

[0075]

[0076]

[0077] in, , , These are the longitude, latitude, and altitude of the radar positioning track point, respectively. , , These are the true value longitude, latitude, and altitude of the waypoint; For east-west speed, For north-south speed, Vertical velocity, The difference between the timestamps of the two points. These are the filtering threshold windows for longitude, latitude, and altitude, respectively.

[0078]

[0079]

[0080]

[0081] in, The time reference error between the two tracks The waypoint number; Step 43: Count the total number of radar positioning track points. Points of successful match The matching degree between the radar-positioned track and the true track is calculated using the following formula:

[0082] When the matching degree At that time, it is determined that the radar positioning track and the true track are successfully matched; Step 44: Associate the successfully matched radar positioning track batch number with the true value track batch number, and store the corresponding track points in the valid database; Step 45: Traverse all radar positioning track data by batch number, repeat steps 41 to 44, and complete all track matching.

[0083] Optionally, after step 4, the method further includes: Step 5: Using the matched track data, adaptively extract and optimize the filtering window threshold and matching degree threshold to obtain the optimized matching parameters.

[0084] Optionally, step 5 includes: Step 51: Select a set of matched and associated radar positioning track data and ground truth track data as parameter optimization samples; Step 52: Using the parameter optimization sample as input data, perform the matching calculations from Step 2 to Step 4. Adjust the size of the filtering window according to the value of the matching degree P obtained in real time, and use the corresponding filtering window threshold as the optimized matching parameter.

[0085] This application also provides an embodiment of a radar positioning track and target true track matching system, which implements the method described in the above embodiment, and includes: The preprocessing module is used to preprocess radar positioning track data and ground truth track data, extract relevant parameters, and convert the relevant parameters into a unified standard format to obtain standardized track data; the relevant parameters include timestamp, longitude, latitude, altitude, and batch number; The parameter initialization module is used to initialize the matching parameters and set the spatial filtering window threshold and track matching degree threshold. The coarse screening module is used to perform invalid value removal, spatial coarse screening, and temporal coarse screening on the standardized track data in sequence using matching parameters to obtain the coarsely screened valid track data. The track matching module is used to compare and match valid track data line by line and point by point based on matching parameters. Point matching is completed by judging the time, longitude, latitude, and altitude window thresholds. The matching degree is obtained by calculating the ratio of the number of successfully matched points in the radar positioning track and the true value track to the total number of points. When the matching degree is not less than the set threshold, the batch number of the corresponding radar positioning track and the true value track is associated to complete the track matching and obtain the matched track data.

[0086] This application also provides an embodiment of an electronic device, including a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, implements the methods described in the above embodiments.

[0087] This application also provides an embodiment of a computer-readable storage medium, the computer-readable storage medium including a computer program or instructions that, when executed on a computer, cause the computer to perform the methods described in the above embodiments.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and not to limit them. Although this application has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of this application. Any modifications or equivalent substitutions that do not depart from the spirit and scope of this application should be covered within the protection scope of the claims of this application.

Claims

1. A method for matching radar positioning tracks with target true tracks, characterized in that, include: Step 1: Preprocess the radar positioning track data and ground truth track data, extract relevant parameters, and convert the relevant parameters into a unified standard format to obtain standardized track data; the relevant parameters include timestamp, longitude, latitude, altitude, and batch number; Step 2: Initialize the matching parameters, and set the spatial filtering window threshold and track matching degree threshold; Step 3: Use matching parameters to sequentially remove invalid values, perform spatial coarse filtering, and temporal coarse filtering on the standardized track data to obtain the coarsely filtered valid track data; Step 4: Based on the matching parameters, perform line-by-line comparison and point-by-point matching of valid track data, and complete point matching by judging the time, longitude, latitude, and altitude window thresholds; The matching degree is obtained by calculating the ratio of the number of points that successfully match the radar positioning track and the true value track to the total number of points. When the matching degree is not less than a set threshold, the batch number of the corresponding radar positioning track and the true value track is associated to complete the track matching and obtain the matched track data.

2. The method according to claim 1, characterized in that, Step 1 includes: Extract timestamps, latitude, longitude, altitude, and batch number from radar positioning track data; extract timestamps, latitude, longitude, altitude, and batch number from ground truth track data; sort the extracted data by batch number, and then sort the data within a single batch by timestamp to obtain standardized track data.

3. The method according to claim 1, characterized in that, Step 2 includes: Step 21: Obtain the radar's maximum detection range As a spatial coarse screening threshold, and to obtain the longitude of radar deployment. ,latitude ,high ; Step 22: Set the spatial filtering window thresholds for longitude, latitude, and altitude. , , and track matching threshold Complete the initialization of matching parameters.

4. The method according to claim 1, characterized in that, Step 3 includes: Step 31: Remove invalid data containing null values ​​or NAN, and remove abnormal data with longitude exceeding ±180°, latitude exceeding ±90°, altitude ≤0, or timestamps that are not positive. Step 32: Based on the latitude and longitude coordinates of the radar deployment and the maximum detection range of the radar The target spatial range is calculated using the following formula: in, , These are the minimum and maximum latitudes for spatial filtering, respectively. , These are the minimum and maximum longitudes for spatial filtering, respectively. This represents the radar's maximum detection range. Remove true track data that is not within the target space range; Step 33: Extract the time interval of radar positioning track and the time interval of the true value track , For the smallest timestamp, For the maximum timestamp, For the smallest timestamp, Maximum timestamp; remove tracks not present in the true value track. Data within; excluding data not present in radar positioning tracks. The data within the data set is then used to perform a coarse screening of radar positioning tracks and true track data, achieving overall alignment of the data distribution in time and space.

5. The method according to claim 1, characterized in that, Step 4 includes: Step 41: Read radar positioning track data by batch number, and retain only valid tracks with a track point count greater than the preset number; read true track data according to the same rules, and retain only valid tracks with a track point count greater than the preset number. Step 42: Using the radar positioning track point as a reference, match it point by point with the true value track point; let the coordinates of the radar positioning track point be... The true track point coordinates are Two-point matching must satisfy the following formula: in, , , These are the longitude, latitude, and altitude of the radar positioning track point, respectively. , , These are the true value longitude, latitude, and altitude of the waypoint; For east-west speed, For north-south speed, Vertical velocity, These are the filtering threshold windows for longitude, latitude, and altitude, respectively. in, The time reference error between the two tracks The difference between the timestamps of the two points. The waypoint number; Step 43: Count the total number of radar positioning track points. Points of successful match The matching degree between the radar-positioned track and the true track is calculated using the following formula: When the matching degree At that time, it is determined that the radar positioning track and the true track are successfully matched; Step 44: Associate the successfully matched radar positioning track batch number with the true value track batch number, and store the corresponding track points in the valid database; Step 45: Traverse all radar positioning track data by batch number, repeat steps 41 to 44, and complete all track matching.

6. The method according to claim 5, characterized in that, After step 4, the following is also included: Step 5: Using the matched track data, adaptively extract and optimize the filtering window threshold and matching degree threshold to obtain the optimized matching parameters.

7. The method according to claim 6, characterized in that, Step 5 includes: Step 51: Select a set of matched and associated radar positioning track data and ground truth track data as parameter optimization samples; Step 52: Using the parameter optimization sample as input data, perform the matching calculations from Step 2 to Step 4. Adjust the size of the filtering window according to the value of the matching degree P obtained in real time, and use the corresponding filtering window threshold as the optimized matching parameter.

8. A radar positioning track and target true track matching system, implementing the method described in any one of claims 1-7, characterized in that, include: The preprocessing module is used to preprocess radar positioning track data and ground truth track data, extract relevant parameters, and convert the relevant parameters into a unified standard format to obtain standardized track data; the relevant parameters include timestamp, longitude, latitude, altitude, and batch number; The parameter initialization module is used to initialize the matching parameters and set the spatial filtering window threshold and track matching degree threshold. The coarse screening module is used to perform invalid value removal, spatial coarse screening, and temporal coarse screening on the standardized track data in sequence using matching parameters to obtain the coarsely screened valid track data. The track matching module is used to compare and match valid track data line by line and point by point based on matching parameters. Point matching is completed by judging the time, longitude, latitude and altitude window thresholds. The matching degree is obtained by calculating the ratio of the number of points that successfully match the radar positioning track and the true value track to the total number of points. When the matching degree is not less than a set threshold, the batch number of the corresponding radar positioning track and the true value track is associated to complete the track matching and obtain the matched track data.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the computer program is executed by the processor, it implements the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a computer program or instructions that, when executed on a computer, cause the computer to perform the method of any one of claims 1-7.

Images