Multi-radar multi-target track fusion data simulation method and device

Abstract

The invention discloses a multi-radar multi-target track fusion data simulation method and device, and relates to the field of radar detection, and the method comprises the steps: determining the positioning error distribution characteristics of a Beidou positioning device according to the positioning error statistics of the Beidou positioning device; according to positioning error distribution characteristics of the Beidou positioning device, Beidou positioning point coordinates of each radar in a geographic coordinate system are simulated; simulating the route of each target according to the parameter data of each target; the detection error distribution characteristics of the radars are determined according to the detection error statistics of the radars; and further simulating detection track point data obtained by detecting each target by each radar. The method fully considers the influence of errors and other factors in the real world, approaches the real effect, can be used as a data source for debugging, testing and testing of the track fusion system, can effectively improve the development efficiency of the track fusion system, and reduces the performance verification cost of the track fusion system.

Description

Technical Field

[0001] The present application relates to the field of radar detection, and in particular to a multi-radar multi-target track fusion data simulation method and device. Background Art

[0002] In the combat of modern air defense weapon systems, track fusion technology is an important means to improve the overall combat effectiveness of the system. In order to accurately perceive and grasp the situation of the target in a complex and changeable battlefield environment, multiple radars are usually used to work together to generate complete and consistent track information through multi-source information fusion. This process can effectively improve the situational awareness capability of the system and provide more accurate decision-making basis for combat command. Therefore, track fusion technology plays an irreplaceable and important role in air defense operations and is an important link in achieving coordinated operations. However, the performance of the track fusion system directly determines the effect of battlefield perception, and a series of tests and verification methods are required to ensure its reliability and applicability in actual combat.

[0003] At present, the testing of track fusion systems mainly relies on field flight tests and radar data acquisition. Although this method can truly reflect the performance of the system, it has the disadvantages of high organizational difficulty and high testing cost. Coordinating multiple radar systems, flight targets and command systems requires a lot of manpower and material resources, and the testing process is complicated. In addition, the testing cost is high, especially when the system needs to be adjusted frequently. Natural environmental restrictions (such as weather, airspace, etc.) further affect the frequency and efficiency of testing, making it difficult to carry out anytime and anywhere, and some typical routes cannot be fully verified. In addition, external factors such as radar positioning accuracy, target detection capability and other variables affect the reliability of test results.

[0004] Therefore, how to provide an efficient and low-cost simulation environment for the test of the track fusion system, which can approach the real combat effect and reduce the interference of external conditions, is an urgent problem that technicians in this field need to solve. Solving this problem will greatly improve the development efficiency of the track fusion system and the accuracy of test verification, and help promote the widespread application of track fusion technology in air defense systems. Summary of the invention

[0005] The purpose of this application is to provide a multi-radar multi-target track fusion data simulation method and device, which can provide a simulation environment close to the real effect for track fusion system testing.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a multi-radar multi-target track fusion data simulation method, comprising:

[0008] According to the positioning error statistics of the Beidou positioning device, the positioning error distribution characteristics of the Beidou positioning device are determined;

[0009] According to the positioning error distribution characteristics of the Beidou positioning device, the Beidou positioning point coordinates of each radar in the geographic coordinate system are simulated;

[0010] According to the parameter data of each target, the route of each target is simulated; the parameter data includes the starting position and the speed, and the route is the time series position data composed of the position of the target at different times, and the time series interval is less than the radar scanning cycle;

[0011] According to the detection error statistics of each radar, the detection error distribution characteristics of each radar are determined;

[0012] According to the Beidou positioning point coordinates of each radar, the detection error distribution characteristics and the route of each target, the detection track point data obtained by each radar for each target is simulated.

[0013] Optionally, the positioning error distribution characteristics of the Beidou positioning device are:

[0014]

[0015] Among them, X Δ is the error of the positioning data of the Beidou positioning device in the x direction, Y Δ is the error of the positioning data of the Beidou positioning device in the y direction, the x direction and the y direction are the directions of the two coordinate axes in the rectangular coordinate system established with the preset position as the coordinate origin, μ is the mean value of the positioning error of the Beidou positioning device, σ b is the standard deviation of the positioning error of the Beidou positioning device, N(μ,σ b 2 ) is the mean value of μ and the value of σ b is the normal distribution of standard deviation, r is the circular probability positioning error of the Beidou positioning device, which is determined according to the positioning error statistics of the Beidou positioning device.

[0016] Optionally, the detection error distribution characteristic of the radar is:

[0017]

[0018] Among them, d Δ ,θ Δ , are the radar’s range error, azimuth error, and elevation error, respectively, d , σ θ , are the standard deviations of range error, azimuth error, and elevation error, respectively. is the mean value of 0 and the value of σ d is the normal distribution with standard deviation, is the mean value of 0 and the value of σ θis the normal distribution with standard deviation, The mean is 0, is a normal distribution with standard deviation.

[0019] Optionally, according to the Beidou positioning point coordinates of each radar, the detection error distribution characteristics and the route of each target, the detection track point data obtained by each radar detecting each target is simulated, specifically including:

[0020] Generate the initial state of each radar in a uniform distribution manner; wherein the initial state is the initial detection azimuth or the initial detection time;

[0021] According to the initial state of each radar, simulate the detection azimuth of each radar at different times;

[0022] According to the Beidou positioning point coordinates of each radar and the route of each target, determine the coordinates of each target at each time in the spherical coordinate system of each radar;

[0023] Determine the position of each target detected by each radar at different times according to the detection azimuth of each radar at different times and the spherical coordinates of each target at different times in the spherical coordinate system of each radar; the spherical coordinates include distance, azimuth and pitch angle;

[0024] According to the detection error distribution characteristics of each radar, an error is added to the position of each target detected by each radar to obtain the detection track point data; the detection track point data includes the detection track points of each radar, wherein the detection track points of the i-th radar are composed of the positions of each target detected by the i-th radar.

[0025] Optionally, determining the position of each target detected by each radar at different times according to the detection azimuth of each radar at different times and the spherical coordinates of each target at different times in the spherical coordinate system of each radar, specifically includes:

[0026] When the difference between the detection azimuth of the ith radar at time t and the azimuth of the jth target in the spherical coordinate system of the ith radar at time t is less than a preset threshold, the spherical coordinates of the jth target in the spherical coordinate system of the ith radar at time t are determined to be the position of the jth target at time t detected by the ith radar. Within 1 / 2 of the radar scanning cycle, there is only one position. Within 1 / 2 of the radar scanning cycle, there is only one position.

[0027] Optionally, according to the positioning error distribution characteristics of the Beidou positioning device, the Beidou positioning point coordinates of each radar in the geographic coordinate system are simulated, and the method also includes:

[0028] Simulate Beidou time and calibrate the clock of each radar and target route simulation.

[0029] In a second aspect, the present application provides a multi-radar multi-target track fusion data simulation device, wherein the multi-radar multi-target track fusion data simulation device applies the multi-radar multi-target track fusion data simulation method described above, and the multi-radar multi-target track fusion data simulation device comprises:

[0030] Beidou position simulation module, used to determine the positioning error distribution characteristics of the Beidou positioning device according to the positioning error statistics of the Beidou positioning device, and simulate the Beidou positioning point coordinates of each radar in the geographic coordinate system according to the positioning error distribution characteristics of the Beidou positioning device;

[0031] A target route simulation module is used to simulate the route of each target according to the parameter data of each target; the parameter data includes the starting position and the speed, and the route is the time series position data composed of the position of the target at different times, and the time series interval is less than the radar scanning period;

[0032] A radar simulation device is used to determine the detection error distribution characteristics of each radar according to the detection error statistics of each radar; simulate the detection track point data obtained by each radar for detecting each target according to the Beidou positioning point coordinates of each radar, the detection error distribution characteristics and the route of each target; the detection track point data includes the detection track points of each target, wherein the detection track points of the jth target are composed of the positions of the jth target detected by each radar at different times.

[0033] Optionally, the multi-radar multi-target track fusion data simulation device further includes:

[0034] Beidou time simulation module is used to simulate Beidou time and calibrate the clock of each radar and target route simulation.

[0035] Optionally, the multi-radar multi-target track fusion data simulation device further includes:

[0036] The communication simulation module is used to simulate the communication transmission delay when each radar sends the position information and detection track point data to the track fusion system.

[0037] Optionally, the multi-radar multi-target track fusion data simulation device further includes:

[0038] The track fusion system is used to associate and fuse the detected track point data.

[0039] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0040] The present application provides a multi-radar multi-target track fusion data simulation method and device, the method comprising: determining the positioning error distribution characteristics of the Beidou positioning device according to the positioning error statistics of the Beidou positioning device; simulating the Beidou positioning point coordinates of each radar in the geographic coordinate system according to the positioning error distribution characteristics of the Beidou positioning device; simulating the route of each target according to the parameter data of each target; the parameter data includes the starting position and speed, the route is the time series position data composed of the position of the target at different times, and the time series interval is much smaller than the radar scanning cycle; determining the detection error distribution characteristics of each radar according to the detection error statistics of each radar respectively; simulating the detection track point data obtained by each radar for each target detection according to the Beidou positioning point coordinates of each radar, the detection error distribution characteristics and the route of each target. The present application fully considers the influence of factors such as errors in the real world, approaches the real effect, can accurately simulate various data in the track fusion process, can be used as the data source for debugging, testing and experimenting of the track fusion system, can effectively improve the development efficiency of the track fusion system, and reduce the performance verification cost of the track fusion system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A schematic diagram of a flow chart of a multi-radar multi-target track fusion data simulation method provided in one embodiment of the present application;

[0043] Figure 2 A flow chart of the target simulation data position coordinate conversion provided by an embodiment of the present application;

[0044] Figure 3 A schematic diagram of the structure of a multi-radar multi-target track fusion data simulation device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0046] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0047] In order to fully verify the fusion performance of the track fusion system in various typical scenarios, it is the best choice to test the track fusion system in a simulated environment. The simulation environment needs to fully consider the influence of factors such as errors in the real world and communication transmission delays, and the ultimate goal is to approach the real effect.

[0048] In an exemplary embodiment, Figure 1 As shown, a multi-radar multi-target track fusion data simulation method is provided, comprising the following steps 101 to 105. Among them:

[0049] Step 101, determining the positioning error distribution characteristics of the Beidou positioning device according to the positioning error statistics of the Beidou positioning device.

[0050] Step 102, simulating the Beidou positioning point coordinates of each radar in the geographic coordinate system according to the positioning error distribution characteristics of the Beidou positioning device; wherein the Beidou positioning device is a device set on the corresponding radar for Beidou positioning of the radar.

[0051] Step 103, simulating the route of each target according to the parameter data of each target; the parameter data includes the starting position and speed, and the route is the time series position data composed of the positions of the target at different times; the time series interval is less than the radar scanning period, and less than here preferably means much less than.

[0052] Step 104, determining the detection error distribution characteristics of each radar based on the detection error statistics of each radar.

[0053] Step 105, based on the Beidou positioning point coordinates of each radar, the detection error distribution characteristics and the route of each target, simulate the detection track point data obtained by each radar for detecting each target.

[0054] Through the above steps 101 to 105, the influence of factors such as errors in the real world is fully considered to approach the real effect, and the various data in the track fusion process can be accurately simulated. It can be used as a data source for debugging, testing, and experimenting of the track fusion system, which can effectively improve the development efficiency of the track fusion system and reduce the performance verification cost of the track fusion system.

[0055] In another exemplary embodiment, the specific implementation of step 101 is as follows:

[0056] (1) The positioning error CEP (Circular Error Probable) of the Beidou positioning device is known to be r. A rectangular coordinate system is established with the preset position as the coordinate origin. Assume that the positioning data of the Beidou positioning device obeys a two-dimensional normal distribution around the preset position. The positioning data errors of the Beidou positioning device are independent and identically distributed in the x and y directions and obey the same normal distribution. Assume that the positioning data error of the Beidou positioning device in the x direction is x Δ , the error in the y direction is Y Δ ,but:

[0057]

[0058] Normally, the mean μ is 0, that is, μ = 0, and the standard deviation is σ b .

[0059] The distance R from the positioning data of the Beidou positioning device to the set point can be expressed as:

[0060] R=(x 2 +y 2 ) 1 / 2 .

[0061] Since x and y are independent and identically distributed, the distribution of R is Rayleigh distribution, and its probability density function f R (r) is:

[0062]

[0063] CEP is defined as the radius of a circle that contains 50% of the hit points, so we need to find the radius R value that makes the Cumulative Distribution Function (CDF) equal to 0.5. The cumulative distribution function F of the Rayleigh distribution R (r) is:

[0064]

[0065] Through integral calculation, the final cumulative distribution function is:

[0066]

[0067] The following equation needs to be solved:

[0068]

[0069] get:

[0070] Since the circular probable positioning error r of the Beidou positioning device can be determined based on the positioning error statistics of the Beidou positioning device, which is a known condition, the error distribution characteristics of the positioning data of the Beidou positioning device in the x and y directions of the rectangular coordinate system can be obtained.

[0071] In another exemplary embodiment, the specific implementation of step 102 is as follows:

[0072] According to the positioning error distribution characteristics, the error of the Beidou positioning device's positioning data in the rectangular coordinate system can be simulated. The Beidou positioning point coordinates of each radar in the geographic coordinate system can be obtained through coordinate conversion.

[0073] In another exemplary embodiment, the specific implementation of step 103 is as follows:

[0074] According to the set target parameters: starting position (x0, y0, z0), set the speed at each moment in the x, y, and z directions by drawing curves, expressed as: v x (t), v y (t), v z (t), then the coordinates of the target at time t (x t ,y t , z t ),in,

[0075] In the target route simulation module, the target position is calculated every 10ms and sent to the radar simulation module.

[0076] In another exemplary embodiment, the specific implementation of step 104 is as follows:

[0077] Radar detection information includes distance d, azimuth θ, pitch angle Usually obey the normal distribution and are independent of each other. That is, radar error:

[0078] Distance error d Δ :

[0079] Azimuth error θ Δ :

[0080] Pitch angle error

[0081] Among them, σ d , σ θ , are the standard deviations of range error, azimuth error, and elevation error, which are usually the characteristics of the radar and are known parameters. Δ ,θ Δ , They are the radar’s distance error, azimuth error, and elevation error, respectively. is the mean value of 0 and the value of σ d is the normal distribution with standard deviation, is the mean value of 0 and the value of σ θ is the normal distribution with standard deviation, The mean is 0, is a normal distribution with standard deviation.

[0082] In another exemplary embodiment, the specific implementation of step 105 is as follows:

[0083] (1) Figure 2 As described above, the route of each target is first converted to the geographic coordinate system, then converted to the rectangular coordinate system with each radar as the origin, and finally converted to the spherical coordinate system with each radar as the origin. The target coordinates are are the distance, azimuth and elevation of the target respectively.

[0084] Radar detection power, that is, the maximum detection distance of the radar d max , which is usually a characteristic of the radar and is a known parameter. max >d m , the radar can detect the target, otherwise the radar cannot detect the target.

[0085] (2) To prevent all radars from detecting the same target at the same time, the initial state of the radar is randomly generated, specifically using a random generation method based on uniform distribution. The initial state is the initial detection azimuth or the initial detection time. This method simulates different starting times or different starting detection azimuths of each radar to prevent the detection azimuths of each radar from starting at the same angle of 0. Taking the initial detection time as an example, assuming that the radar azimuth scanning period is T, when the test system starts working, the initial detection time t0 of the radar follows a uniform distribution, recorded as t0~Uniform(0,T), and the initial azimuth is 0.

[0086] (3) Simulate radar azimuth scanning of aerial targets. The radar azimuth scanning only detects the azimuth at a certain moment and rotates clockwise or counterclockwise according to the scanning period T. The radar azimuth scanning range is [0°, 360°). When the radar azimuth scanning angle is equal to the target azimuth angle θ m When the difference is less than the preset threshold, the radar detects the target and generates the target coordinates at time t as This coordinate is consistent with the Consistent, within the time T / 2, there is only one target coordinate.

[0087] At this time, combined with the above errors, the coordinates of the radar detection target are obtained for:

[0088] d=d t +d Δ ;

[0089] θ=θ t +θ Δ ;

[0090]

[0091] In another exemplary embodiment, the present application also provides steps of Beidou time simulation and communication simulation.

[0092] Among them, the data types of Beidou time simulation include: year, month, day, hour, minute, second, and millisecond. The communication simulation is used to simulate the communication transmission delay of the radar's Beidou positioning point coordinates and detection track point data.

[0093] In an exemplary embodiment, Figure 3 As shown, a multi-radar multi-target track fusion data simulation device is provided, and the multi-radar multi-target track fusion data simulation device comprises:

[0094] The Beidou position simulation module is used to determine the positioning error distribution characteristics of the Beidou positioning device according to the positioning error statistics of the Beidou positioning device, and simulate the Beidou positioning point coordinates of each radar in the geographic coordinate system according to the positioning error distribution characteristics of the Beidou positioning device.

[0095] The target route simulation module is used to simulate the route of each target according to the parameter data of each target; the parameter data includes the starting position and speed, and the route is the time series position data composed of the position of the target at different times, and the time series interval is less than the radar scanning cycle.

[0096] A radar simulation device is used to determine the detection error distribution characteristics of each radar according to the detection error statistics of each radar; simulate the detection track point data obtained by each radar for detecting each target according to the Beidou positioning point coordinates of each radar, the detection error distribution characteristics and the route of each target; the detection track point data includes the detection track points of each target, wherein the detection track points of the jth target are composed of the positions of the jth target detected by each radar at different times.

[0097] In an exemplary embodiment, Figure 3 As shown, the present application also provides a Beidou time simulation module and a communication simulation module.

[0098] The above modules are run in various computer devices in the form of software programs, and data communication is carried out through switches.

[0099] The radar simulation device includes a plurality of radar simulation modules.

[0100] Among them, the Beidou time simulation module is used to simulate Beidou time and periodically send Beidou time to the target route simulation module and each radar simulation module. The periodicity is a fixed value. After receiving the Beidou time, the target route simulation module and each radar simulation module adjust the time of each device to be consistent with the Beidou time. Beidou time data types include: year, month, day, hour, minute, second, and millisecond.

[0101] The Beidou position simulation module is used to simulate the Beidou positioning information of each radar. In the test system, the Beidou position simulation module is used to set the position of each radar in the geographic coordinate system. The position data includes: radar ID, longitude, latitude, and altitude. The positioning data generation cycle of the Beidou positioning device is a fixed value. In the Beidou position simulation module, the position of each radar can be uniformly set to form a multi-radar detection deployment. The positioning data of the Beidou positioning device is sent to each radar simulation module with a period of 100ms. Since there are errors in the positioning of Beidou equipment, the positioning error is usually described by the circular error probability (CEP). Therefore, the Beidou position simulation module needs to simulate the positioning data of the Beidou positioning device with errors of each radar.

[0102] The target route simulation module is used to simulate the flight of an aerial target, including setting the target flight route and generating the target's current flight parameters in time sequence according to the target flight route. The target flight parameters include: target time sequence position, target enemy attributes, speed, target ID, etc. The target time sequence position is the X, Y, and Z in the rectangular coordinate system relative to the position of the track fusion system in the geographic coordinate system. The target route simulation module can set the air target route parameters, including: target ID, starting position (x0, y0, z0), speed (v x ,v y ,v z ), enemy and friendly attributes (enemy aircraft, friendly aircraft, unknown, etc.), time. After the target is set, the target movement is simulated according to the time sequence, and the target flight parameter data is sent to each radar simulation module.

[0103] The radar simulation module is used to simulate the radar's detection track of the target. The radar simulation module receives the position data sent by the Beidou position simulation module to form radar position data; receives the target flight parameter data sent by the target route simulation module, simulates the detection of the target according to the radar scanning cycle and radar characteristics, and generates real-time detection track point data. The radar characteristics include: radar detection power, radar detection error, and the radar scanning cycle is a fixed value. Each radar simulation module sends the detection track point data and radar position data to the communication simulation module. The detection track point data includes: target ID, enemy and friend attributes, distance, azimuth, pitch angle, and detection time. Among them, the distance, azimuth, and pitch angle are spherical coordinates with the radar as the coordinate origin. The radar position data includes: radar ID, longitude, latitude, and altitude.

[0104] The communication simulation module is used to simulate the delay of data in the communication process. The communication simulation module sends the received detection track point data and radar position data to the track fusion system after a certain delay. The delay is usually a fixed value and can be set according to the actual situation. After receiving the detection track point data and radar position data, the track fusion system associates and fuses the tracks of multiple radars and multiple targets.

[0105] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0106] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A multi-radar multi-target track fusion data simulation method, characterized in that: include: According to the positioning error statistics of the Beidou positioning device, the positioning error distribution characteristics of the Beidou positioning device are determined; According to the positioning error distribution characteristics of the Beidou positioning device, the Beidou positioning point coordinates of each radar in the geographic coordinate system are simulated; According to the parameter data of each target, the route of each target is simulated; the parameter data includes the starting position and speed, and the route is the time series position data composed of the position of the target at different times; the time series interval is less than the radar scanning cycle; According to the detection error statistics of each radar, the detection error distribution characteristics of each radar are determined; According to the Beidou positioning point coordinates of each radar, the detection error distribution characteristics and the route of each target, the detection track point data obtained by each radar for each target is simulated.

2. The multi-radar multi-target track fusion data simulation method according to claim 1 is characterized in that: The positioning error distribution characteristics of the Beidou positioning device are: Among them, X Δ is the error of the positioning data of the Beidou positioning device in the x direction, Y Δ is the error of the positioning data of the Beidou positioning device in the y direction, the x direction and the y direction are the directions of the two coordinate axes in the rectangular coordinate system established with the preset position as the coordinate origin, μ is the mean value of the positioning error of the Beidou positioning device, σ b is the standard deviation of the positioning error of the Beidou positioning device, is the mean value μ and the b is the normal distribution of standard deviation, r is the circular probability positioning error of the Beidou positioning device, which is determined according to the positioning error statistics of the Beidou positioning device.

3. The multi-radar multi-target track fusion data simulation method according to claim 1 is characterized in that: The detection error distribution characteristics of radar are: Among them, d Δ ,θ Δ , are the radar’s range error, azimuth error, and elevation error, respectively, d , σ θ , are the standard deviations of range error, azimuth error, and elevation error, respectively. is the mean value of 0 and the value of σ d is the normal distribution with standard deviation, is the mean value of 0 and the value of σ θ is the normal distribution with standard deviation, The mean is 0, is a normal distribution with standard deviation.

4. The multi-radar multi-target track fusion data simulation method according to claim 1 is characterized in that: According to the Beidou positioning point coordinates of each radar, the detection error distribution characteristics and the route of each target, the detection track point data obtained by each radar for each target detection is simulated, including: Generate the initial state of each radar in a uniform distribution manner; wherein the initial state is the initial detection azimuth or the initial detection time; According to the initial state of each radar, simulate the detection azimuth of each radar at different times; According to the Beidou positioning point coordinates of each radar and the route of each target, determine the coordinates of each target at each time in the spherical coordinate system of each radar; Determine the position of each target detected by each radar at different times according to the detection azimuth of each radar at different times and the spherical coordinates of each target at different times in the spherical coordinate system of each radar; the spherical coordinates include distance, azimuth and pitch angle; According to the detection error distribution characteristics of each radar, an error is added to the position of each target detected by each radar to obtain the detection track point data; the detection track point data includes the detection track points of each radar, wherein the detection track points of the i-th radar are composed of the positions of each target detected by the i-th radar.

5. The multi-radar multi-target track fusion data simulation method according to claim 4 is characterized in that: According to the detection azimuth of each radar at different times and the spherical coordinates of each target at different times in the spherical coordinate system of each radar, the position of each target detected by each radar at different times is determined, specifically including: When the difference between the detection azimuth of the ith radar at time t and the azimuth of the jth target in the spherical coordinate system of the ith radar at time t is less than a preset threshold, the spherical coordinates of the jth target in the spherical coordinate system of the ith radar at time t are determined to be the position of the jth target at time t detected by the ith radar, and there is only one position within a time period of 1 / 2 of the radar scanning cycle.

6. The multi-radar multi-target track fusion data simulation method according to claim 1 is characterized in that: According to the positioning error distribution characteristics of the Beidou positioning device, the Beidou positioning point coordinates of each radar in the geographic coordinate system are simulated, which also includes: Simulate Beidou time and calibrate the clock of each radar and target route simulation.

7. A multi-radar multi-target track fusion data simulation device, characterized in that: The multi-radar multi-target track fusion data simulation device applies the multi-radar multi-target track fusion data simulation method according to any one of claims 1 to 6, and the multi-radar multi-target track fusion data simulation device comprises: Beidou position simulation module, used to determine the positioning error distribution characteristics of the Beidou positioning device according to the positioning error statistics of the Beidou positioning device, and simulate the Beidou positioning point coordinates of each radar in the geographic coordinate system according to the positioning error distribution characteristics of the Beidou positioning device; A target route simulation module is used to simulate the route of each target according to the parameter data of each target; the parameter data includes the starting position and the speed, and the route is the time series position data composed of the position of the target at different times, and the time series interval is less than the radar scanning period; A radar simulation device is used to determine the detection error distribution characteristics of each radar according to the detection error statistics of each radar; simulate the detection track point data obtained by each radar for detecting each target according to the Beidou positioning point coordinates of each radar, the detection error distribution characteristics and the route of each target; the detection track point data includes the detection track points of each target, wherein the detection track points of the jth target are composed of the positions of the jth target detected by each radar at different times.

8. The multi-radar multi-target track fusion data simulation device according to claim 7 is characterized in that: The multi-radar multi-target track fusion data simulation device also includes: Beidou time simulation module is used to simulate Beidou time and calibrate the clock of each radar and target route simulation.

9. The multi-radar multi-target track fusion data simulation device according to claim 7, characterized in that: The multi-radar multi-target track fusion data simulation device also includes: The communication simulation module is used to simulate the communication transmission delay when each radar sends the position information and detection track point data to the track fusion system.

10. The multi-radar multi-target track fusion data simulation device according to claim 7, characterized in that: The multi-radar multi-target track fusion data simulation device also includes: The track fusion system is used to associate and fuse the detected track point data.

Images