Target track association method and device based on space-time grid

Abstract

The invention discloses a time-space grid-based target track association method and device. The method comprises the following steps: acquiring track data information at a T moment, track data information at a T + 1 moment, a track data set at the T moment and time-space grid information; t is a positive integer; performing fusion processing on the T-moment track data information, the space-time grid information and the T-moment track data set to obtain T-moment track fusion result information; and carrying out fusion processing on the T moment track fusion result information, the space-time grid information and the T + 1 moment track data information to obtain target track information. According to the method, the global multi-source targets are put into the space-time grids, and the association degree between the targets is calculated, so that the rapid association of the target tracks can be realized, the whole-course target tracking of the multi-source targets is realized, the calculation complexity is reduced, and the fusion efficiency and accuracy of the association of the multi-source targets are improved.

Description

Technical Field

[0001] The present invention relates to the field of information fusion, and in particular to a target track association method and device based on time-space grid. Background Art

[0002] Track association is the comprehensive processing of target track information obtained by multiple radar sensors. It uses information association, registration, prediction and other methods to obtain the global track of the target as accurately and comprehensively as possible, achieve high-precision and continuous target tracking, and thus more comprehensively reflect the comprehensive situation of the target. Traditional information fusion methods mainly include data preprocessing, coordinate transformation, time-space alignment, track association, track filtering and other links, and finally obtain the complete track corresponding to each target.

[0003] However, in the real-time association of multi-source target tracks, it is necessary to quickly classify various point tracks and track data of different sensors and different targets, and then form target track association through spatiotemporal relationships, feature associations, etc., to achieve clustering of track information and feature data of the same target on a target data set, with objective requirements such as fast, stable, and accurate. When processing the far sea and far domain situation data, it has the characteristics of large number of targets, large amount of data, and high update rate. Traditional information fusion algorithms are prone to problems such as low accuracy of association fusion in interlaced tracks or dense target environments, and the amount of calculation increases exponentially with the number of targets, and the amount of calculation is often difficult to cope with. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a target track association method and device based on a space-time grid. By placing global multi-source targets into a space-time grid and calculating the correlation between targets, it is possible to achieve rapid association of target tracks, thereby achieving full-process target tracking of multi-source targets, which is beneficial to reducing calculation complexity and improving the fusion efficiency and accuracy of multi-source target association.

[0005] In order to solve the above technical problems, the first aspect of the embodiment of the present invention discloses a target track association method based on a spatiotemporal grid, the method comprising:

[0006] S1, obtain track data information at time T, track data information at time T+1, track data set at time T and space-time grid information; the track data set at time T includes a plurality of fused track data information; the fused track data information includes fused track speed information, fused track average speed information, fused track position information, fused track time information and fused track batch number value; the space-time grid information includes a plurality of time level grid information and a plurality of space level grid information; the time level grid information includes a plurality of time grid information; the space level grid information includes a plurality of space grid information; T is a positive integer;

[0007] S2, fusing the track data information at time T, the spatiotemporal grid information and the track data set at time T to obtain track fusion result information at time T;

[0008] S3, fusing the track fusion result information at time T, the spatiotemporal grid information and the track data information at time T+1 to obtain target track information.

[0009] As an optional implementation, in the first aspect of the embodiment of the present invention, the fusion processing of the track data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track fusion result information at time T includes:

[0010] S21, preprocessing the track data information at time T to obtain preprocessed track data information at time T;

[0011] S22, extracting the pre-processed track data information at time T to obtain track extracted data information at time T; the track extracted data information at time T includes first track position information, first track speed information, first track average speed information, first track time information and first track batch number value;

[0012] S23, processing the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain track fusion result information at time T.

[0013] As an optional implementation, in the first aspect of the embodiment of the present invention, the processing of the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track fusion result information at time T includes:

[0014] S231, performing matching processing on the first track batch number value and the track data set at time T to obtain matching result information and fused track matching data information;

[0015] When the matching result information is negative, execute S232;

[0016] When the matching result information is yes, execute S234;

[0017] S232, adding the track extraction data information at time T to the track data set at time T;

[0018] S233, obtaining first track data information to be processed, and determining that the first track data information to be processed is the track data information at time T, and executing S2;

[0019] S234, processing the track extraction data information at time T, the spatiotemporal grid information, the fused track matching data information and the track data set at time T to obtain track fusion result information at time T.

[0020] As an optional implementation, in the first aspect of the embodiment of the present invention, the processing of the track extraction data information at time T, the spatiotemporal grid information, the fused track matching data information and the track data set at time T to obtain the track fusion result information at time T includes:

[0021] S2341, calculating and processing the track extraction data information at time T and the fused track matching data information to obtain a track correlation value at time T;

[0022] S2342, determining whether the track correlation value at time T is greater than a first correlation threshold, and obtaining a first determination result;

[0023] When the first judgment result is yes, execute S2343;

[0024] When the first judgment result is no, executing S2344;

[0025] S2343, fusing the track extraction data information at time T with the fused track matching data information to obtain the track result information at time T, and executing S2345;

[0026] S2344, processing the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track result information at time T;

[0027] S2345, adding the track result information at time T to the track fusion result information at time T;

[0028] S2346, obtaining the user's first stop receiving instruction information;

[0029] When the user stops receiving the first instruction information, the step of executing S3 is yes;

[0030] When the first user stops receiving the instruction information is no, the second track data information to be processed is obtained, and it is determined that the second track data information to be processed is the track data information at the time T, and S2 is executed.

[0031] As an optional implementation, in the first aspect of the embodiment of the present invention, the calculating and processing the track extraction data information at time T and the fused track matching data information to obtain the track correlation value at time T includes:

[0032] S23411, calculating and processing the first track position information and the fused track position information in the fused track matching data information to obtain a distance correlation value;

[0033] S23412, calculating and processing the first track speed information and the fused track speed information in the fused track matching data information to obtain a speed correlation value;

[0034] S23413, performing weighted average calculation processing on the distance correlation value and the speed correlation value to obtain a motion attribute correlation value;

[0035] S23414, performing average calculation processing on the first track average speed information and the fused track average speed information in the fused track matching data information to obtain an average speed correlation value;

[0036] S23415, determining whether the motion attribute association value is greater than the average speed association value, and obtaining a second determination result;

[0037] When the second judgment result is yes, determining the motion attribute association value as the track association value at time T;

[0038] When the second judgment result is no, the average speed correlation value is determined to be the track correlation value at the time T.

[0039] As an optional implementation, in the first aspect of the embodiment of the present invention, the processing of the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track result information at time T includes:

[0040] S23441, matching the first track time information, the first track position information and the space-time grid information to obtain target-level time grid information and target-level space grid information;

[0041] S23442, performing matching processing on the first track time information, the first track position information, the target level time grid information and the target level space grid information to obtain target time grid information and target space grid information;

[0042] S23443, processing the track data set at time T, the spatiotemporal grid information, the target time grid information and the target space grid information to obtain a plurality of fused track data information to be processed;

[0043] S23444, processing a plurality of the fused track data information to be processed and the track extraction data information at time T to obtain the track result information at time T.

[0044] As an optional implementation, in the first aspect of the embodiment of the present invention, the fusion processing of the track fusion result information at time T, the spatiotemporal grid information and the track data information at time T+1 to obtain the target track information includes:

[0045] S31, processing the track fusion result information at time T to obtain predicted fused track information at time T+1; the predicted fused track information at time T+1 includes a plurality of predicted track information at time T+1;

[0046] S32, obtaining the track data set at time T+1;

[0047] S33, processing the predicted fused track information at time T+1, the spatiotemporal grid information, the track data information at time T+1 and the track data set at time T+1 to obtain target track fusion result information and target track information;

[0048] S34, obtaining the user's second stop receiving instruction information;

[0049] When the second stop receiving instruction information of the user is no, T is increased by 1, the third track data information to be processed is obtained, and the third track data information to be processed is determined to be the track data information at time T+1, and the target track fusion result information is the target track fusion result information at time T, and S31 is executed;

[0050] When the user's second stop receiving instruction information is yes, the process ends.

[0051] A second aspect of an embodiment of the present invention discloses a target track association device based on a spatiotemporal grid, the device comprising:

[0052] An acquisition module is used to acquire track data information at time T, track data information at time T+1, track data set at time T and space-time grid information; the track data set at time T includes a plurality of fused track data information; the fused track data information includes fused track speed information, fused track average speed information, fused track position information, fused track time information and fused track batch number value; the space-time grid information includes a plurality of time level grid information and a plurality of space level grid information; the time level grid information includes a plurality of time grid information; the space level grid information includes a plurality of space grid information; T is a positive integer;

[0053] A first calculation module is used to fuse the track data information at time T, the spatiotemporal grid information and the track data set at time T to obtain track fusion result information at time T;

[0054] The second calculation module is used to fuse the track fusion result information at time T, the space-time grid information and the track data information at time T+1 to obtain the target track information.

[0055] A third aspect of an embodiment of the present invention discloses another target track association device based on a spatiotemporal grid, the device comprising:

[0056] processor;

[0057] a memory coupled to the processor and storing executable program code;

[0058] The processor calls the executable program code stored in the memory to execute part or all of the steps of the target track association method based on the space-time grid disclosed in the first aspect of the embodiment of the present invention.

[0059] A fourth aspect of an embodiment of the present invention discloses a computer-readable storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all steps of the target track association method based on time-space grid disclosed in the first aspect of the embodiment of the present invention.

[0060] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0061] In an embodiment of the present invention, track data information at time T, track data information at time T+1, a track data set at time T and space-time grid information are obtained; the track data set at time T includes a plurality of fused track data information; the fused track data information includes fused track speed information, fused track average speed information, fused track position information, fused track time information and fused track batch number value; the space-time grid information includes a plurality of time level grid information and a plurality of space level grid information; the time level grid information includes a plurality of time grid information; the space level grid information includes a plurality of space grid information; T is a positive integer; the track data information at time T, the space-time grid information and the track data set at time T are fused to obtain the track fusion result information at time T; the track fusion result information at time T, the space-time grid information and the track data information at time T+1 are fused to obtain the target track information. It can be seen that this embodiment can realize the rapid association of target tracks by placing global multi-source targets into a space-time grid and calculating the correlation between targets, thereby realizing full-process target tracking of multi-source targets, which is beneficial to reducing the computational complexity and improving the fusion efficiency and accuracy of multi-source target association. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0063] Figure 1 A schematic diagram of a flow chart of a target track association method based on a spatiotemporal grid disclosed in an embodiment of the present invention;

[0064] Figure 2 A schematic diagram of the structure of a target track association device based on a time-space grid disclosed in an embodiment of the present invention;

[0065] Figure 3 The present invention is a schematic structural diagram of another target track association device based on a time-space grid disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0066] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or equipment.

[0068] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0069] It should be noted that the time grid in this application refers to the time grid information in this application.

[0070] The present invention discloses a target track association method and device based on a time-space grid, which can realize the rapid association of target tracks by placing global multi-source targets into the time-space grid and calculating the correlation between targets, thereby realizing the full-range target tracking of multi-source targets, which is beneficial to reducing the computational complexity and improving the fusion efficiency and accuracy of multi-source target association. The following are detailed descriptions.

[0071] Embodiment 1

[0072] See also Figure 1 , Figure 1 is a flow chart of a target track association method based on a spatiotemporal grid disclosed in an embodiment of the present invention. Figure 1 The described target track association method based on the space-time grid is applied to a target track association device based on the space-time grid, such as a local server or cloud server for optimizing the association management of target tracks based on the space-time grid, and the embodiments of the present invention are not limited thereto. Figure 1 As shown, the target track association method based on the space-time grid may include the following operations:

[0073] S1, obtain the track data information at time T, the track data information at time T+1, the track data set at time T and the space-time grid information; the track data set at time T includes a number of fused track data information; the fused track data information includes fused track speed information, fused track average speed information, fused track position information, fused track time information and fused track batch number value; the space-time grid information includes a number of time level grid information and a number of space level grid information; the time level grid information includes a number of time grid information; the space level grid information includes a number of space grid information; T is a positive integer;

[0074] It should be noted that the track data information at time T is the track data information received by any sensor among the multi-source sensors (radar, camera, etc.) at time T; the track data information at time T+1 is the track data information received by any sensor among the multi-source sensors at time T+1; the track data set at time T is the track data information that has been associated with the target and fused at time T.

[0075] It should be noted that the fused track time information is the average time of the reconnaissance cycle of multiple sensors after fusion in the fused track data information. For example, the fused track data information is obtained by associating and fusing the data of two sensors, and the corresponding reconnaissance cycles of the two sensors are 10s and 30s respectively, then the fused track time information is (10+30) / 2=20s.

[0076] S2, fusing the track data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track fusion result information at time T;

[0077] S3, fusing the track fusion result information at time T, the spatiotemporal grid information and the track data information at time T+1 to obtain the target track information.

[0078] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0079] In an optional embodiment, obtaining spatiotemporal grid information includes:

[0080] S11, using the Beidou navigation system to synchronize the time information of all sensors in the multi-source sensor and initialize the time of each sensor;

[0081] S12, obtaining the reconnaissance detection time period values ​​of all sensors in the multi-source sensor;

[0082] S13, calculating the lowest common divisor of the reconnaissance detection time period values ​​of all sensors to obtain the lowest common value of the sensors;

[0083] S14, sorting the reconnaissance detection time period values ​​of all sensors in ascending order to obtain sorted reconnaissance detection time period values;

[0084] S15, determining a lower limit value of the time resolution based on the sorted reconnaissance detection time period values; the lower limit value of the time resolution is the first reconnaissance detection time period value among the sorted reconnaissance detection time period values;

[0085] S16, determining the lowest common denominator of the sensors as the upper limit of the time resolution;

[0086] S17, dividing the difference between the upper limit value of the time resolution and the lower limit value of the time resolution into a number of equal parts to obtain a number of time level grid information;

[0087] It should be noted that the above-mentioned several equal divisions are divided into 8 equal divisions.

[0088] S18, performing grid division processing on any time level grid information to obtain a plurality of time grid information of the time level grid information;

[0089] S19, based on all sensors in the multi-source sensor, determining a plurality of spatial level grid information.

[0090] For example, the number of time level grid information is 8, the lower limit of the time resolution is 30ms, and the upper limit of the time resolution is 1500ms. The difference is 1500ms-30ms=1470ms, and then 8 equal divisions are made into 1470ms / 8=183.75ms. The obtained 8 time level grid information are as follows:

[0091] The first time level grid information: 30ms (lower limit of time resolution, highest accuracy);

[0092] The second time level grid information: 30ms+183.75ms=213.75ms;

[0093] The third time level grid information: 213.75ms+183.75ms=397.5ms;

[0094] …

[0095] The eighth time level grid information: 1500ms (upper limit of time resolution, minimum accuracy)

[0096] The above-mentioned grid division processing of any time level grid information to obtain several time grid information of the time level grid information is performed by using the time level grid information within a given time interval, such as the time interval [A1, A2]. For example, the first time level grid information is 30ms, and [A1, A2] is divided to obtain the time grid information corresponding to the time level grid information [A1, A1+30ms], [A1+30ms, A1+30ms+30ms]...[A2-30ms, A2].

[0097] It should be noted that the lower limit of the time resolution is based on the shortest reconnaissance cycle to ensure that no sensor data is lost. The upper limit of the time resolution is based on the lowest common denominator to ensure that the data of all sensors can be aligned in the same time grid information for easy fusion. In this way, the time area is divided into 8 different levels of time resolution, and the time resolution of each level is different, which allows analysis and processing for different time scales. If the shortest reconnaissance cycle of the sensor corresponding to the track data information at time T is small, the low-level time level grid information can be used to reduce the amount of calculation. If the shortest reconnaissance cycle of the sensor corresponding to the track data information at time T is large, the high-level time level grid information is used to ensure accuracy.

[0098] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0099] In an optional embodiment, based on all sensors in the multi-source sensor, several spatial level grid information is determined, including:

[0100] S191, obtaining longitude component values, latitude component values, and elevation component values ​​of reconnaissance errors of all sensors in the multi-source sensor;

[0101] S192, determining that the minimum value of the longitude component values ​​of all sensors is the minimum longitude grid spatial resolution, and the lowest common divisor of the longitude component values ​​of all sensors is the maximum longitude grid spatial resolution;

[0102] S193, determining that the minimum value of the latitude component values ​​of all sensors is the minimum latitude grid spatial resolution, and the lowest common divisor of the latitude component values ​​of all sensors is the maximum latitude grid spatial resolution;

[0103] S194, determining that the minimum value of the elevation component values ​​of all sensors is the minimum elevation grid spatial resolution, and the lowest common divisor of the elevation component values ​​of all sensors is the maximum elevation grid spatial resolution;

[0104] S195, obtaining the longitude value and latitude value of the track data information at time T and the maximum reconnaissance range value of the sensor corresponding to the track data information at time T on the elevation component;

[0105] S196, determining the maximum reconnaissance range value as an elevation value;

[0106] S197, using the 2000 Chinese Geodetic Coordinate System (CGCS2000) adopted by the BeiDou Navigation System, divides the minimum longitude grid spatial resolution, the maximum longitude grid spatial resolution, the minimum latitude grid spatial resolution, the maximum latitude grid spatial resolution, the minimum elevation grid spatial resolution and the maximum elevation grid spatial resolution into equal intervals in the three dimensions of longitude, latitude and elevation, and combines them in the three dimensions to obtain several spatial level grid information;

[0107] It should be noted that the above-mentioned plurality of spatial level grid information is 8 spatial level grid information;

[0108] S198, dividing any one of the plurality of spatial level grid information to obtain a plurality of spatial level grid information.

[0109] Exemplarily, the above-obtained plurality of spatial level grid information can be processed as follows:

[0110] It should be noted that the above S197-S198 can be divided by tools such as ArcGIS or QGIS, and the specific embodiment of the present invention is not limited thereto.

[0111] It should be noted that, like the above-mentioned time level raster information, the above-mentioned 8 spatial level raster information have different hierarchical levels. The first spatial level raster information has the smallest resolution and the highest accuracy, and the eighth spatial level raster information has the largest resolution and the lowest accuracy.

[0112] It should be noted that by selecting the minimum value of the error components of each sensor as the minimum grid spatial resolution, the system can ensure that the errors of all sensors have a high accuracy, so that the spatial grid can be refined. In this way, the position of the target can be more accurately located in target tracking and prediction. By selecting the lowest common divisor of all sensor errors as the maximum grid resolution, it is ensured that the error range of all sensors can be covered in the division of the spatial range, so that no important information will be missed during data fusion, and the compatibility and consistency of the fusion results are also ensured.

[0113] It should be noted that by dividing the space with different resolutions, the computing tasks can be performed in a unified hierarchy and structure. Select appropriate minimum and maximum resolution values ​​to optimize the computing process and avoid over-division (too high spatial resolution) and over-simplification (too low spatial resolution). This spatial division method helps reduce unnecessary calculations and improves the operating efficiency of the system.

[0114] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0115] In an optional embodiment, the track data information at time T, the spatiotemporal grid information and the track data set at time T are fused to obtain the track fusion result information at time T, including:

[0116] S21, preprocessing the track data information at time T to obtain preprocessed track data information at time T;

[0117] It should be noted that the above preprocessing includes data verification, time synchronization, coordinate transformation, data cleaning, etc., which can be processed by Pandas, Chrony, ArcGIS and Pandas respectively, and the specific embodiment of the present invention is not limited.

[0118] It should be noted that the above data verification can check whether the track data information at time T contains necessary information such as the target's timestamp, position, speed, etc., and can filter out invalid or abnormal data.

[0119] It should be noted that the above time synchronization uses a global clock (such as GPS time) to unify the timestamp to calibrate the time base of the track data information at time T. Since data from different sensors may have different time bases, time calibration is required.

[0120] It should be noted that if the data comes from different coordinate systems (such as polar coordinates of radar and image coordinates of camera), it needs to be converted to a unified global coordinate system. The above coordinate transformation can convert the track data information at time T into global Cartesian coordinate information.

[0121] It should be noted that the above data cleaning uses filters (such as mean filtering and Kalman filtering) to remove high-frequency noise and exclude abnormal data (such as impossible speed or distance) that exceeds a preset range.

[0122] S22, extracting the pre-processed track data information at time T to obtain the track extracted data information at time T; the track extracted data information at time T includes first track position information, first track speed information, first track average speed information, first track time information and first track batch number value;

[0123] It should be noted that the above extraction operation can be performed using tools such as Numpy and MATLAB, and the specific details are not limited in the embodiments of the present invention.

[0124] It should be noted that the first track time information is the reconnaissance cycle time value of the sensor corresponding to the pre-processed track data information at time T, such as 10s.

[0125] S23, processing the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track fusion result information at time T.

[0126] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0127] In another optional embodiment, the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T are processed to obtain the track fusion result information at time T, including:

[0128] S231, matching the first track batch number value with the track data set at time T to obtain matching result information and fused track matching data information;

[0129] When the matching result information is negative, execute S232;

[0130] When the matching result information is yes, execute S234;

[0131] S232, adding the track extraction data information at time T to the track data set at time T;

[0132] S233, obtaining the first track data information to be processed, and determining that the first track data information to be processed is the track data information at time T, and executing S2;

[0133] It should be noted that the first track data information to be processed is the track data information received by any sensor at time T.

[0134] S234, processing the track extraction data information at time T, the spatiotemporal grid information, the fused track matching data information and the track data set at time T to obtain the track fusion result information at time T.

[0135] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0136] In an optional embodiment, matching processing is performed on the first track batch number value and the track data set at time T to obtain matching result information and fused track matching data information, including:

[0137] S2311, preset s=1;

[0138] S2312, judging whether the first track batch number value is equal to the fused track batch number value in the s-th fused track data information in the track data set at time T, and obtaining a third judgment result;

[0139] When the third judgment result is yes, it is determined to be matching result information, and the s-th fused track data information is determined to be fused track matching data information;

[0140] When the third judgment result is no, it is determined whether s is equal to the amount of fused track data information in the track data set at time T, and a fourth judgment result is obtained;

[0141] When the fourth judgment result is no, s is increased by 1 and S2312 is executed;

[0142] When the fourth judgment result is yes, it is determined whether it is matching result information, and the s-th fused track data information is determined to be fused track matching data information.

[0143] It should be noted that when the third judgment result is yes, the matching result information is set to yes; when the third judgment result is no, the matching result information is set to no; when the fourth judgment result is yes, the matching result information is set to no.

[0144] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0145] In another optional embodiment, the track extraction data information at time T, the spatiotemporal grid information, the fused track matching data information and the track data set at time T are processed to obtain the track fusion result information at time T, including:

[0146] S2341, calculating and processing the track extraction data information and the fused track matching data information at time T to obtain the track correlation value at time T;

[0147] S2342, determining whether the track correlation value at time T is greater than a first correlation threshold, and obtaining a first determination result;

[0148] When the first judgment result is yes, execute S2343;

[0149] When the first judgment result is no, execute S2344;

[0150] S2343, fusing the track extraction data information at time T with the fused track matching data information to obtain the track result information at time T, and executing S2345;

[0151] It should be noted that the above fusion processing can obtain the track result information at time T, which can be processed by JPDA and a multi-target tracking algorithm. Specifically, the embodiment of the present invention does not limit this.

[0152] S2344, processing the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track result information at time T;

[0153] S2345, adding the track result information at time T to the track fusion result information at time T;

[0154] S2346, obtaining the user's first stop receiving instruction information;

[0155] When the user first stops receiving the instruction information, the answer is yes, executing S3;

[0156] When the first user stops receiving the instruction information is no, the second track data information to be processed is obtained, and it is determined that the second track data information to be processed is the track data information at time T, and S2 is executed.

[0157] It should be noted that the second track data information to be processed is the track data information received by any sensor at time T.

[0158] It should be noted that the first correlation threshold may be set by a user or obtained based on historical data, and the embodiment of the present invention does not make any specific limitation thereto.

[0159] The purpose of judging whether the track correlation value at time T is greater than the first correlation threshold is to ensure the correct association of the target and avoid mis-association. Through threshold screening, the system can improve the accuracy of data processing, ensure the accuracy of target tracking and prediction, and avoid erroneous fusion of the tracks of different targets, which helps to improve the reliability and effectiveness of target track association of multi-source sensors.

[0160] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0161] In an optional embodiment, the track extraction data information and the fused track matching data information at time T are calculated and processed to obtain the track correlation value at time T, including:

[0162] S23411, calculating and processing the first track position information and the fused track position information in the fused track matching data information to obtain a distance correlation value;

[0163] It should be noted that the first correlation calculation model is used to calculate and process the first track position information and the fused track position information in the fused track matching data information to obtain a distance correlation value;

[0164] Among them, the first correlation calculation model is:

[0165]

[0166] 0≤δ1,δ2≤1;

[0167] δ1+δ2=1;

[0168] Wherein, JL is the distance correlation value, HJ is the first track position information, RH is the fused track position information, (HJX, HJY, HJZ) is the coordinate of the first track position information, (RHX, RHY, RHZ) is the coordinate of the fused track position information, TC is the square of the standard error of the sensor corresponding to the first track position information, δ1 and δ2 represent the first weight parameter and the second weight parameter respectively, and ||·|| represents modulus;

[0169] It should be noted that the first weight parameter and the second weight parameter may be set by a user or may be obtained based on historical data, which is not limited in the embodiment of the present invention.

[0170] It should be noted that the standard error of the sensor corresponding to the first track position information is obtained by acquiring parameter information of the sensor.

[0171] It should be noted that the coordinate information in this application is coordinate information corresponding to the Cartesian coordinate system.

[0172] It should be noted that by adjusting these two weight parameters, the influence of position similarity and direction similarity on the correlation value can be flexibly controlled. Specifically, if more attention is paid to the spatial position similarity of the track, a larger δ2 can be set; if more attention is paid to the directional matching of the track, a larger δ1 can be set.

[0173] Through the first correlation calculation model, it is possible to effectively evaluate whether the tracks observed by different sensors belong to the same physical target.

[0174] S23412, calculating and processing the first track speed information and the fused track speed information in the fused track matching data information to obtain a speed correlation value;

[0175] It should be noted that the second correlation calculation model is used to calculate and process the first track speed information and the fused track speed information in the fused track matching data information to obtain a speed correlation value;

[0176] Among them, the second correlation calculation model is:

[0177]

[0178] 0≤δ3,δ4≤1;

[0179] δ3+δ4=1;

[0180] Wherein, SD is the speed correlation value, HS is the first track speed information, RS is the fused track speed information, ||·|| represents modulus, |·| represents absolute value, δ3 and δ4 represent the third weight coefficient and the fourth weight coefficient, and ρ represents the constant coefficient.

[0181] It should be noted that the third weight coefficient, the fourth weight coefficient and the constant coefficient may be set by a user, or may be obtained based on historical data, and the embodiment of the present invention does not limit this.

[0182] It should be noted that the second correlation calculation model can reflect the matching of the two dimensions of speed and direction. By adjusting the weight coefficient, the importance of speed and direction in the final correlation value can be flexibly controlled, which helps to accurately evaluate the speed similarity of the target track in multi-source sensor data fusion, thereby achieving more efficient target association.

[0183] It should be noted that by setting the constant coefficient, a reasonable correlation can be maintained under slight error conditions, while avoiding low confidence or boundary conditions that cause the correlation to be directly zero.

[0184] S23413, performing weighted average calculation processing on the distance correlation value and the speed correlation value to obtain a motion attribute correlation value;

[0185] S23414, performing average calculation processing on the first track average speed information and the fused track average speed information in the fused track matching data information to obtain an average speed correlation value;

[0186] S23415, determining whether the motion attribute correlation value is greater than the average speed correlation value, and obtaining a second determination result;

[0187] When the second judgment result is yes, determine the motion attribute correlation value as the track correlation value at time T;

[0188] When the second judgment result is no, the average speed correlation value is determined as the track correlation value at time T.

[0189] It should be noted that the motion attribute correlation value focuses more on the instantaneous distance and speed matching, while the average speed correlation value reflects the long-term trend characteristics of the target movement. This judgment logic can be biased towards short-term or long-term information when necessary, thereby achieving comprehensive consideration; when the target movement changes dramatically, the system can still capture the global characteristics of the target through the average speed; when the movement is stable, the motion attribute correlation is more accurate.

[0190] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0191] In an optional embodiment, the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T are processed to obtain the track result information at time T, including:

[0192] S23441, matching the first track time information, the first track position information and the space-time grid information to obtain target level time grid information and target level space grid information;

[0193] It should be noted that the above matching process is to match which time level grid information in the spatiotemporal grid information the first track time information belongs to, and to match which space level grid information in the spatiotemporal grid information the first track position information belongs to, and to use the matched time level grid information and space level grid information as the target level time grid information and target level space grid information. The specific matching process can be performed using QGIS or ArcGIS, which is not limited in the embodiments of the present invention.

[0194] S23442, matching the first track time information, the first track position information, the target level time grid information, and the target level space grid information to obtain the target time grid information and the target space grid information;

[0195] It should be noted that the above matching process is to match which time grid information in the target level time grid information the first track time information belongs to, and which space grid information in the target level space grid information the first track position information belongs to, and the matched time grid information and space grid information are used as the target time grid information and target space grid information. For the specific matching process, QGIS or ArcGIS can be used for matching process, which is not limited in the embodiment of the present invention.

[0196] S23443, processing the track data set at time T, the spatiotemporal grid information, the target time grid information, and the target space grid information to obtain a plurality of fused track data information to be processed;

[0197] It should be noted that the above processing of the track data set at time T, the space-time grid information, the target time grid information and the target space grid information to obtain a number of fused track data information to be processed is to determine whether the fused track data information in the track data set at time T exists in the target time grid information and the target space grid information. If it exists, the fused track data information is used as a fused track data information to be processed. If not, it continues to determine whether the fused track data information in the track data set at time T exists in the 8 time grid information adjacent to the target time grid information and the 8 space grid information adjacent to the target space grid information, and the matched fused track data information is used as a fused track data information to be processed. The specific processing can be processed using QGIS or ArcGIS, which is not limited in the embodiments of the present invention.

[0198] It should be noted that the above processing ensures efficient association of dynamic targets under complex spatiotemporal conditions. Direct matching is the core and extended search is the supplement. The two complement each other, ensuring the accuracy of matching and enhancing the ability to adapt to uncertainty, ensuring the computational efficiency under big data processing.

[0199] S23444, processing a number of to-be-processed fused track data information and track extraction data information at time T to obtain track result information at time T.

[0200] It should be noted that the above-mentioned processing of the plurality of to-be-processed fused track data information and the track extraction data information at time T can be processed by JPDA and a multi-target tracking algorithm, which is not limited in detail in the embodiment of the present invention.

[0201] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0202] In an optional embodiment, the track fusion result information at time T, the spatiotemporal grid information and the track data information at time T+1 are fused to obtain the target track information, including:

[0203] S31, processing the track fusion result information at time T to obtain the predicted fused track information at time T+1; the predicted fused track information at time T+1 includes a plurality of predicted track information at time T+1;

[0204] S32, obtaining the track data set at time T+1;

[0205] S33, processing the predicted fused track information at time T+1, the spatiotemporal grid information, the track data information at time T+1, and the track data set at time T+1 to obtain target track fusion result information and target track information;

[0206] S34, obtaining the user's second stop receiving instruction information;

[0207] When the second stop receiving instruction information of the user is no, T is increased by 1, the third track data information to be processed is obtained, and the third track data information to be processed is determined to be the track data information at time T+1, and the target track fusion result information is the target track fusion result information at time T, and S31 is executed;

[0208] When the user's second stop receiving instruction information is yes, the process ends.

[0209] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0210] In an optional embodiment, the track fusion result information at time T is processed to obtain the predicted fused track information at time T+1; the predicted fused track information at time T+1 includes several pieces of predicted track information at time T+1, including:

[0211] Using the track prediction calculation model, the track fusion result information at time T is processed to obtain the predicted fusion track information at time T+1;

[0212] Among them, the track prediction calculation model is:

[0213] HJS i =ZY·SDD i +KZ·KZ i +ZS1≤i≤N;

[0214] Where, HJS is the predicted fusion track information at time T+1, HJS i is the predicted track information of the ith T+1 time in the predicted fusion track information at T+1 time, ZY represents the state transfer matrix, SDD i is the i-th track result information at time T in the track fusion result information at time T, KZ is the control input matrix, KZ i is the control vector corresponding to the i-th track result information at time T in the track fusion result information at time T, ZS is the noise constant vector, and N is the number of track result information at time T in the track fusion result information at time T.

[0215] It should be noted that the state transfer matrix, the control input matrix and the noise constant vector may be set by the user or obtained based on historical data, which is not limited in the embodiment of the present invention.

[0216] It should be noted that the control vector KZ i It is the acceleration vector of the i-th track result information at time T in the track fusion result information at time T.

[0217] It should be noted that by introducing the noise constant vector, in dynamic target tracking, the noise constant vector can be used to compensate for the uncertainty of target motion (such as the target suddenly changes speed or direction). By introducing the noise constant vector, the T+1 time prediction fusion track information obtained can more flexibly adapt to the non-stationary behavior of the target.

[0218] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0219] In an optional embodiment, the predicted fused track information at time T+1, the spatiotemporal grid information, the track data information at time T+1, and the track data set at time T+1 are processed to obtain target track fusion result information and target track information, including:

[0220] S331, processing the track data information at time T+1, the spatiotemporal grid information and the track data set at time T+1 to obtain target track fusion result information;

[0221] It should be noted that the track data information at time T+1, the spatiotemporal grid information and the track data set at time T+1 are processed to obtain the target track fusion result information, which can be obtained by processing according to step S2 of the present invention.

[0222] S332, calculating and processing the track fusion result information at time T+1 and the predicted fusion track information at time T+1 to obtain the target track information.

[0223] It should be noted that the track fusion result information at time T+1 and the predicted fused track information at time T+1 are calculated and processed to obtain the target track information, which can be processed by JPDA and multi-target tracking algorithm, and the embodiment of the present invention does not limit it. Specifically, the track fusion result information at time T+1 and the predicted fused track information at time T+1 are associated with the time grid information and space grid information. If there is only one target to be associated in the current time grid information and space grid information, the fused target is directly associated with the original track. If there is no target to be associated in the current grid, the search range is expanded to the 8 time grid information and space grid information adjacent to the current time grid information and space grid information for association. If there are multiple targets to be associated within the search range (the current time grid information and space grid information or the 8 time grid information and space grid information adjacent to the current grid), the Euclidean distance between the track fusion result information at time T+1 and each target to be associated is calculated, and the target to be associated with the smallest distance is associated. After the target association is completed, the track result information at time T in the track fusion result information at time T that matches the target to be associated is selected for fusion processing to obtain the target fusion track information. The target fusion track information is then added to the target track information.

[0224] It should be noted that the T time track result information in the T time track fusion result information matching the target to be associated is selected for fusion processing to obtain the target fusion track information, which is to fuse the T+1 time track result information in the T+1 time track fusion result information with the T time track result information in the T time track fusion result information to obtain the target fusion track information. The fusion processing is processed by JPDA and the multi-target tracking algorithm, which is not limited in the embodiment of the present invention.

[0225] It can be seen that the target track association method based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the computational complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0226] Embodiment 2

[0227] See also Figure 2 , Figure 2 : is a schematic diagram of a target track association device based on a time-space grid disclosed in an embodiment of the present invention. Figure 2 The described target track association device based on the time-space grid is applied to the target track association optimization system based on the time-space grid, such as a local server or cloud server for target track association based on the time-space grid, which is not limited in the embodiment of the present invention. Figure 2 As shown, the target track association device based on the time-space grid includes:

[0228] The acquisition module 201 is used to acquire the track data information at time T, the track data information at time T+1, the track data set at time T and the time-space grid information; the track data set at time T includes a plurality of fused track data information; the fused track data information includes fused track speed information, fused track average speed information, fused track position information, fused track time information and fused track batch number value; the time-space grid information includes a plurality of time level grid information and a plurality of space level grid information; the time level grid information includes a plurality of time grid information; the space level grid information includes a plurality of space grid information; T is a positive integer;

[0229] The first calculation module 202 is used to fuse the track data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track fusion result information at time T;

[0230] The second calculation module 203 is used to fuse the track fusion result information at time T, the space-time grid information and the track data information at time T+1 to obtain the target track information.

[0231] It can be seen that the target track association device based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the calculation complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0232] Embodiment 3

[0233] See also Figure 3 , Figure 3 is a schematic diagram of the structure of another target track association device based on a time-space grid disclosed in an embodiment of the present invention. Figure 3 The described target track association device based on time-space grid is applied to a target track association optimization system based on time-space grid, such as a local server or cloud server for target track association based on time-space grid, which is not limited in the embodiments of the present invention.

[0234] like Figure 3As shown, the target track association device based on the time-space grid includes:

[0235] Processor 301;

[0236] A memory 302 coupled to the processor 301 and storing executable program codes;

[0237] The processor 301 calls the executable program code stored in the memory 302 to execute part or all of the steps of the target track association method based on the space-time grid of the first embodiment.

[0238] It can be seen that the target track association device based on the space-time grid described in the embodiment of the present invention can realize the full-range target tracking of multi-source targets, which is beneficial to reduce the calculation complexity and improve the fusion efficiency and accuracy of multi-source target association.

[0239] Embodiment 4

[0240] The embodiment of the present invention discloses a computer-readable storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all steps of the target track association method based on time-space grid in embodiment 1.

[0241] Embodiment 5

[0242] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute some or all of the steps in the target track association method based on a spatiotemporal grid described in the first embodiment.

[0243] The system embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative labor.

[0244] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0245] Finally, it should be noted that the target track association method and device based on the space-time grid disclosed in the embodiment of the present invention discloses only the preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that it is still possible to modify the technical solutions recorded in the aforementioned embodiments, or to replace some of the technical features therein by equivalents. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A target track association method based on a spatiotemporal grid, characterized in that: The method comprises: S1, obtain track data information at time T, track data information at time T+1, track data set at time T and space-time grid information; the track data set at time T includes a plurality of fused track data information; the fused track data information includes fused track speed information, fused track average speed information, fused track position information, fused track time information and fused track batch number value; the space-time grid information includes a plurality of time level grid information and a plurality of space level grid information; the time level grid information includes a plurality of time grid information; the space level grid information includes a plurality of space grid information; T is a positive integer; S2, fusing the track data information at time T, the spatiotemporal grid information and the track data set at time T to obtain track fusion result information at time T; S3, fusing the track fusion result information at time T, the spatiotemporal grid information and the track data information at time T+1 to obtain target track information.

2. The target track association method based on time-space grid according to claim 1 is characterized in that: The fusing process of the track data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track fusion result information at time T includes: S21, preprocessing the track data information at time T to obtain preprocessed track data information at time T; S22, extracting the pre-processed track data information at time T to obtain track extracted data information at time T; the track extracted data information at time T includes first track position information, first track speed information, first track average speed information, first track time information and first track batch number value; S23, processing the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain track fusion result information at time T.

3. The target track association method based on time-space grid according to claim 2 is characterized in that: The processing of the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track fusion result information at time T includes: S231, performing matching processing on the first track batch number value and the track data set at time T to obtain matching result information and fused track matching data information; When the matching result information is negative, execute S232; When the matching result information is yes, execute S234; S232, adding the track extraction data information at time T to the track data set at time T; S233, obtaining first track data information to be processed, and determining that the first track data information to be processed is the track data information at time T, and executing S2; S234, processing the track extraction data information at time T, the spatiotemporal grid information, the fused track matching data information and the track data set at time T to obtain track fusion result information at time T.

4. The target track association method based on time-space grid according to claim 3 is characterized in that: The processing of the track extraction data information at time T, the spatiotemporal grid information, the fused track matching data information and the track data set at time T to obtain the track fusion result information at time T includes: S2341, calculating and processing the track extraction data information at time T and the fused track matching data information to obtain a track correlation value at time T; S2342, determining whether the track correlation value at time T is greater than a first correlation threshold, and obtaining a first determination result; When the first judgment result is yes, execute S2343; When the first judgment result is no, executing S2344; S2343, fusing the track extraction data information at time T with the fused track matching data information to obtain the track result information at time T, and executing S2345; S2344, processing the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track result information at time T; S2345, adding the track result information at time T to the track fusion result information at time T; S2346, obtaining the user's first stop receiving instruction information; When the user stops receiving the first instruction information, the step of executing S3 is yes; When the first user stops receiving the instruction information, the second track data information to be processed is obtained, and it is determined that the second track data information to be processed is the track data information at the time T, and S2 is executed.

5. The target track association method based on time-space grid according to claim 4 is characterized in that: The calculating and processing the track extraction data information at time T and the fused track matching data information to obtain the track correlation value at time T includes: S23411, calculating and processing the first track position information and the fused track position information in the fused track matching data information to obtain a distance correlation value; S23412, calculating and processing the first track speed information and the fused track speed information in the fused track matching data information to obtain a speed correlation value; S23413, performing weighted average calculation processing on the distance correlation value and the speed correlation value to obtain a motion attribute correlation value; S23414, performing average calculation processing on the first track average speed information and the fused track average speed information in the fused track matching data information to obtain an average speed correlation value; S23415, determining whether the motion attribute association value is greater than the average speed association value, and obtaining a second determination result; When the second judgment result is yes, determining the motion attribute association value as the track association value at time T; When the second judgment result is no, the average speed correlation value is determined to be the track correlation value at the time T.

6. The target track association method based on time-space grid according to claim 4 is characterized in that: The processing of the track extraction data information at time T, the spatiotemporal grid information and the track data set at time T to obtain the track result information at time T includes: S23441, matching the first track time information, the first track position information and the space-time grid information to obtain target-level time grid information and target-level space grid information; S23442, performing matching processing on the first track time information, the first track position information, the target level time grid information and the target level space grid information to obtain target time grid information and target space grid information; S23443, processing the track data set at time T, the spatiotemporal grid information, the target time grid information and the target space grid information to obtain a plurality of fused track data information to be processed; S23444, processing a plurality of the fused track data information to be processed and the track extraction data information at time T to obtain the track result information at time T.

7. The target track association method based on time-space grid according to claim 1 is characterized in that: The step of fusing the track fusion result information at time T, the space-time grid information and the track data information at time T+1 to obtain target track information includes: S31, processing the track fusion result information at time T to obtain predicted fused track information at time T+1; the predicted fused track information at time T+1 includes a plurality of predicted track information at time T+1; S32, obtaining the track data set at time T+1; S33, processing the predicted fused track information at time T+1, the spatiotemporal grid information, the track data information at time T+1 and the track data set at time T+1 to obtain target track fusion result information and target track information; S34, obtaining the user's second stop receiving instruction information; When the second stop receiving instruction information of the user is no, T is increased by 1, the third track data information to be processed is obtained, and the third track data information to be processed is determined to be the track data information at time T+1, and the target track fusion result information is the target track fusion result information at time T, and S31 is executed; When the user's second stop receiving instruction information is yes, the process ends.

8. A target track association device based on a time-space grid, characterized in that: The device comprises: An acquisition module is used to acquire track data information at time T, track data information at time T+1, track data set at time T and space-time grid information; the track data set at time T includes a plurality of fused track data information; the fused track data information includes fused track speed information, fused track average speed information, fused track position information, fused track time information and fused track batch number value; the space-time grid information includes a plurality of time level grid information and a plurality of space level grid information; the time level grid information includes a plurality of time grid information; the space level grid information includes a plurality of space grid information; T is a positive integer; A first calculation module is used to fuse the track data information at time T, the spatiotemporal grid information and the track data set at time T to obtain track fusion result information at time T; The second calculation module is used to fuse the track fusion result information at time T, the space-time grid information and the track data information at time T+1 to obtain the target track information.

9. A target track association device based on a time-space grid, characterized in that: The device comprises: processor; a memory coupled to the processor and storing executable program code; The processor calls the executable program code stored in the memory to execute the target track association method based on the space-time grid as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the target track association method based on the space-time grid according to any one of claims 1 to 7.

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