A target discrimination method and system based on moving track and radar device

Abstract

The application provides a target discrimination method and system based on a moving track and a radar device, and belongs to the technical field of security and protection systems. The method comprises the following steps: determining a defense zone boundary in combination with the area shape of the defense zone; dividing the defense zone by using a square grid, and giving each grid a unique number and a corresponding weight value; judging whether a target is in the defense zone according to the position information of the defense zone boundary; if the target is outside the defense zone, the target is recorded and continuously monitored; if the target crosses the defense zone boundary and enters the defense zone, the target is given a defense zone identifier, the grid where the target is located is determined, the moving track of the target is predicted according to the position of the target, the weight value of the target is calculated based on the weight value of the grid where the target is located on the moving track in the defense zone, and whether the target is a real target is judged. The beneficial effects of the technical scheme of the application are that the properties of the moving target can be well discriminated, the pseudo target can be excluded, the real nature of the target can be effectively identified, and the identification ability of the radar for detecting the target can be improved.

Description

Technical Field

[0001] This invention belongs to the field of security system technology, and more specifically, relates to a target discrimination method, system and radar equipment based on moving trajectory. Background Technology

[0002] The security industry, a crucial manifestation of urbanization and informatization, has become a rigid demand for urban development, playing a vital role in various sectors such as urban security management, production supervision, emergency command, and traffic management. In recent years, with the support of fundamental capabilities in networks, data, computing, chips, and algorithms, and the efficient application of technologies such as the Internet of Things, big data, and artificial intelligence, security technologies have found widespread application in various security products. Simultaneously, the development of security technology has gradually changed the demands of security applications, giving rise to area-based security equipment, such as microwave radar and lidar, based on traditional linear security devices. This enables real-time protection of key area locations and enriches the types of security products. Today, major security product manufacturers have introduced radar equipment as the primary means of area-based security monitoring, fully utilizing radar's advantages such as strong anti-interference capabilities, wide range, and continuous three-dimensional monitoring. By scanning with radar, they can collect real-time information on the location of intrusion targets, achieving continuous target acquisition and effectively addressing the protection challenges of various area-based security zones. Related equipment has already been successfully applied in industries such as petrochemicals, transportation, and border defense.

[0003] Most existing security radars use microwave detection technology to acquire the position, speed, and height information of moving targets in real time. They can capture targets well in relatively clean environments. However, in environments with lush vegetation, the reflected spectrum acquired by the radar is greatly affected by the vegetation. The interference signal generated by the swaying of vegetation is very similar to the signal generated by the human body in terms of height and speed, thus forming a large number of interference signals. The system itself has difficulty making correct judgments on the radar detection signals, resulting in a large number of false alarms.

[0004] To address the issue of vegetation interference with existing radar equipment, a common approach is to eliminate false targets. This involves removing the interference area from the defense zone to improve alarm accuracy. However, this often results in missed alarms due to insufficient precision in defining the interference area. Summary of the Invention

[0005] In order to solve the problems existing in the prior art, the present invention provides a target discrimination method, system and radar equipment based on moving trajectory, which can effectively distinguish the authenticity of moving targets, eliminate false targets, thereby effectively identifying the authenticity of targets and improving the radar's target identification capability.

[0006] To achieve the above objectives, the present invention provides a target discrimination method based on a moving trajectory, comprising:

[0007] Step S1: Determine the boundary of the defense zone based on the shape of the defense zone, and set the location information of the defense zone boundary;

[0008] Step S2: Divide the defense zone into square grids and assign a unique number and corresponding weight value to each grid;

[0009] Step S3: Detect the target signal, determine whether the target is inside the defense zone based on the position information of the defense zone boundary. If the target is outside the defense zone, record and continuously monitor the target. If the target crosses the defense zone boundary and enters the defense zone, proceed to step S4.

[0010] Step S4: Assign a defense zone identifier to the target, determine the grid in which the target is located, and predict the movement trajectory based on the target's location;

[0011] Step S5: When the target moves within the defense zone, calculate the weight value of the target based on the weight value corresponding to the grid where the target's movement trajectory is located, and determine whether the target is a real target. Alternatively, when the target does not move within its grid and the detection signal disappears, mark the grid as an active grid so that when the target reappears, directly assign a defense zone identifier to the target and enter the movement trajectory prediction. Or, when the target exits from its grid to outside the defense zone, remove the target's defense zone identifier and switch to the outside target monitoring state.

[0012] Preferably, in step S5, when the target moves within the defense zone, a weight value is calculated for the target based on the weight value corresponding to the grid where the target's movement trajectory is located, and it is determined whether the target is a real target. This specifically includes:

[0013] Step S51: Based on the grid where the target is located, determine the grids adjacent to that grid within the defense zone as valid prediction grids;

[0014] Step S52: If the target moves to an adjacent grid, the weight value of the target is accumulated; if the target moves to another grid outside the effective prediction grid, the weight value of the target is subtracted.

[0015] Step S53: Repeat steps S51 and S52 based on the target movement trajectory until the target weight value is greater than or equal to the preset upper limit of the weight threshold, then the target movement trajectory is determined to be real; or, if the target weight value is less than or equal to the preset lower limit of the weight threshold, then the target movement trajectory is determined to be abnormal.

[0016] Preferably, in step S3, one or more targets outside the defense zone are continuously monitored.

[0017] Preferably, the weight values ​​of the grid are set individually or uniformly.

[0018] Preferably, the size of the square grid is 2m × 2m.

[0019] The present invention also provides a target discrimination system based on a moving trajectory, the system comprising:

[0020] The zone boundary setting module is used to determine the zone boundary based on the shape of the zone and to set the location information of the zone boundary.

[0021] The defense zone meshing module is used to divide the defense zones into square grids and assign a unique number and corresponding weight value to each grid.

[0022] The signal monitoring module is used to detect target signals and record and continuously monitor the target when it is outside the defense zone;

[0023] The signal location determination module is used to determine whether the target is within the defense zone based on the location information of the defense zone boundary.

[0024] A movement trajectory prediction module is used to assign a defense zone identifier to a target when it crosses the defense zone boundary and enters the defense zone, determine the grid where the target is located, and predict its movement trajectory based on the target's location. The movement trajectory prediction module includes:

[0025] The first processing submodule is used to calculate the weight value of the target based on the weight value corresponding to the grid where the target's movement trajectory is located when the target moves within the defense zone, and to determine whether the target is a real target.

[0026] The second processing submodule is used to mark the grid as an active grid when the target has not moved and the detection signal has disappeared, so that when the target reappears, the defense zone identifier can be directly assigned to the target and the movement trajectory prediction can be entered.

[0027] The third processing submodule is used to remove the target's defense zone identifier and switch to the outside-defense zone monitoring state when the target exits the grid where it is located and moves to the outside of the defense zone.

[0028] Preferably, the first processing submodule includes:

[0029] An effective prediction grid determination unit is used to determine, based on the grid where the target is located, the grids adjacent to that grid within the defense zone as effective prediction grids;

[0030] The weight value calculation unit is used to accumulate the weight value of the target when the target moves to an adjacent grid, or to subtract the weight value of the target when the target moves to another grid outside the effective prediction grid.

[0031] The movement trajectory discrimination unit is used to discriminate the calculated target weight value based on the target movement trajectory. If the target weight value is greater than or equal to the preset upper limit of the weight threshold, the target movement trajectory is judged to be real; or, if the target weight value is less than or equal to the preset lower limit of the weight threshold, the target movement trajectory is judged to be abnormal.

[0032] Preferably, the weight values ​​of the grid are set individually or uniformly.

[0033] Preferably, the size of the square grid is 2m × 2m.

[0034] The present invention also provides a radar device, the radar device including the target discrimination system based on the moving trajectory as described above.

[0035] The beneficial effects of the technical solution of the present invention are as follows:

[0036] This invention, based on target information detected by radar and combined with defense zone boundary and internal attribute information, analyzes the correlation between target location information and the defense zone, assigns defense zone identifiers, applies grid weights, and combines this with the target's movement trajectory. This allows for effective identification of moving targets, eliminating false targets and thus enhancing the radar's target identification capabilities. This invention is applicable to large-scale monitoring scenarios, such as border lines, waterways, and nature reserves. It can identify targets quickly and continuously record target movement trajectories, providing data support for later evidence collection and incident handling.

[0037] Furthermore, under normal circumstances, it is difficult for personnel and animals to make continuous positional changes at 2-meter intervals. Therefore, setting the square grid inside the defense zone to 2m×2m significantly reduces false alarms. Especially in monitoring scenarios with relatively dense vegetation, since the movement of vegetation theoretically will not exceed two squares (i.e., 4 meters), interference caused by vegetation movement can be effectively filtered out, further improving the target identification effect and solving the problem of existing radar equipment being interfered with by vegetation. Attached Figure Description

[0038] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the invention.

[0039] Figure 1 A flowchart illustrating a target discrimination method based on a moving trajectory provided in an embodiment of the present invention;

[0040] Figure 2 A flowchart illustrating step S5 of a target discrimination method based on a moving trajectory provided in an embodiment of the present invention;

[0041] Figure 3 This invention provides a target discrimination method based on movement trajectory, which includes a prediction map of the movement trajectory of a target entering the defense zone boundary.

[0042] Figure 4 This is a schematic diagram of a target discrimination system based on a moving trajectory, provided in an embodiment of the present invention.

[0043] Explanation of reference numerals in the attached figures:

[0044] 1. Zone boundary setting module; 2. Zone gridding module; 3. Signal monitoring module; 4. Signal position judgment module; 5. Movement trajectory prediction module; 51. First processing submodule; 52. Second processing submodule; 53. Third processing submodule; 511. Effective prediction grid determination unit; 512. Weight value calculation unit; 513. Movement trajectory discrimination unit. Detailed Implementation

[0045] Preferred embodiments of the invention will now be described in more detail. While preferred embodiments of the invention are described below, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0046] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0047] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but this is not intended to limit the scope of the invention.

[0048] Example 1

[0049] Reference Figure 1 As shown, this embodiment provides a target discrimination method based on movement trajectory, including:

[0050] Step S1: Determine the boundary of the defense zone based on its shape, and set the location information of the defense zone boundary;

[0051] Step S2: Divide the defense zones into square grids and assign a unique number and corresponding weight value to each grid;

[0052] Step S3: Detect the target signal and determine whether the target is inside the defense zone based on the position information of the defense zone boundary. If the target is outside the defense zone, record and continuously monitor the target. If the target crosses the defense zone boundary and enters the defense zone, proceed to step S4.

[0053] Step S4: Assign a defense zone identifier to the target, determine the grid in which the target is located, and predict the movement trajectory based on the target's location;

[0054] Step S5: When the target moves within the defense zone, calculate the weight value of the target based on the weight value corresponding to the grid where the target's movement trajectory is located, and determine whether the target is a real target. Alternatively, when the target does not move within its grid and the detection signal disappears, mark the grid as an active grid so that when the target reappears, directly assign a defense zone identifier to the target and enter the movement trajectory prediction. Or, when the target exits from its grid to outside the defense zone, remove the target's defense zone identifier and switch to the outside target monitoring state.

[0055] Specifically, the defense zone is a polygonal area. Based on the zone's protection requirements, its boundaries are determined. The radar and the zone boundary are positioned relative to each other. After setting the zone boundary position information, every point on the boundary has position information. The interior of the defense zone is set as a square grid, with each grid assigned a unique number (numeric, alphanumeric, or a combination of both) and a weight value. When the radar detects a target signal, it first determines the target's location and assigns it a unique ID. When a target is outside the defense zone, it only needs to be recorded and continuously monitored. When a target enters the defense zone boundary, a defense zone identification attribute is added to the target. Based on the defense zone identification attribute, the target's movement trajectory is predicted according to its location. When the target moves within the defense zone, a weight value is calculated based on the weight value corresponding to the grid where the target's movement trajectory is located, and it is determined whether the target is a real target. When the weight value reaches the upper limit of the preset weight threshold, it is identified as a real target. Alternatively, when the target does not move within its grid and the detection signal disappears, the grid is marked as an active grid so that when the target reappears, a defense zone identification attribute is directly assigned to the target and movement trajectory prediction is entered. The purpose of marking the grid as an active grid is that when the target reappears, it is not necessary to determine whether it has crossed the defense zone boundary; the target is directly assigned a defense zone identification attribute and enters movement trajectory prediction. In other words, a target that just disappeared in a grid within the defense zone is reactivated, thus avoiding missing the target. Alternatively, when the target exits from its grid to outside the defense zone, the target's defense zone identification attribute is removed, movement trajectory prediction is canceled, and the system switches to outside-defense zone target monitoring status. When a radar detects a target signal, its detection data typically includes the target ID, position, speed, and altitude information. Based on the target information detected by the radar, by analyzing the correlation between the target position information and the defense zone boundary, and based on the defense zone boundary and internal attribute information, by assigning a defense zone identifier and applying a grid weighting method, combined with the target's movement trajectory, it is possible to effectively distinguish between real and false moving targets, eliminate false targets, and thus effectively identify the authenticity of the target and improve the radar's target identification capability.

[0056] A preferred example, see Figure 2As shown, in step S5, when the target moves within the defense zone, a weight value is calculated for the target based on the weight value corresponding to the grid on the target's movement trajectory within the defense zone, and it is determined whether the target is a real target. Specifically, this includes:

[0057] Step S51: Based on the grid where the target is located, determine the grids adjacent to that grid within the defense zone as valid prediction grids;

[0058] Step S52: If the target moves to an adjacent grid, the weight value of the target is accumulated; if the target moves to another grid outside the effective prediction grid, the weight value of the target is subtracted.

[0059] Step S53: Repeat steps S51 and S52 based on the target movement trajectory until the target weight value is greater than or equal to the preset upper limit of the weight threshold, then the target movement trajectory is determined to be real; or, if the target weight value is less than or equal to the preset lower limit of the weight threshold, then the target movement trajectory is determined to be abnormal.

[0060] Specifically, in the trajectory prediction process, the grids adjacent to the target grid are the target trajectory prediction grids, and only by moving to an adjacent grid can the target be identified as the real target. For example... Figure 3 As shown, the square grids within the defense zone are numbered, and each grid has a weight value of 1. In this embodiment, the upper limit of the weight threshold is set to 3, and the lower limit of the weight threshold is set to -5. After the radar detects a target enters the defense zone, its position is grid number 3, and the target's weight value is 1. Based on the grid where the target is located, the grids adjacent to it are effective prediction grids. There are 6 possible positions for the target to move to: grid numbers 2, 7, 8, 9, 4, or to cross the defense zone boundary and leave the defense zone.

[0061] When a target moves from grid number 3 to a valid predicted grid (i.e., to any one of grid numbers 2, 7, 8, 9, or 4), its weight value is incremented by 1. Based on the target's movement trajectory, the weight value is accumulated for each valid predicted grid it moves to. Once the weight value reaches 3 or higher, the target's movement trajectory is considered real, indicating a movable target, such as the movement trajectory of personnel, animals, or vehicles. If the target moves directly from grid number 3 to a grid outside its predicted grid position within the defense zone, the weight value is decremented by 1. Once the weight value reaches -5 or higher, the target's movement trajectory is considered abnormal. This algorithm accumulates and subtracts weight values ​​based on the grids corresponding to the target's movement trajectory, has low complexity, is simple to implement, and can identify targets quickly. It can also effectively detect abnormal trajectories involving grid jumps.

[0062] In a preferred example, in step S3, one or more targets outside the defense zone are continuously monitored.

[0063] Specifically, by continuously monitoring one or more targets outside the defense zone, especially in scenarios involving multiple targets, the efficiency of multi-target search and discovery can be improved.

[0064] In a preferred example, the weight values ​​of the grid are set individually or uniformly.

[0065] Specifically, for different monitoring scenarios, adjusting the grid weight parameters helps improve the accuracy of the weight algorithm, further enhancing the accuracy of the method in detecting targets.

[0066] In a preferred example, the size of the square grid is 2m × 2m.

[0067] Specifically, under normal circumstances, it is difficult for personnel and animals to make continuous positional changes at 2-meter intervals. Therefore, setting the square grid within the defense zone to 2m×2m significantly reduces false alarms. Especially in monitoring scenarios with relatively dense vegetation, the irregular swaying of vegetation due to wind generates a large amount of interference, particularly in height and speed information, which is highly similar to human feature detection data. If a target detected by vegetation does not cross the defense zone boundary, it will not be assigned a defense zone identification attribute, thus not triggering target trajectory prediction. Even if it crosses the defense zone boundary due to wind, theoretically, based on the swaying position of the vegetation, it will not exceed two squares (i.e., 4 meters). The 2m×2m square grid setting can effectively filter out the interference caused by vegetation swaying, further improving the target identification effect and solving the problem of existing radar equipment being interfered with by vegetation. In special cases, the size of the square grid can be adjusted as appropriate.

[0068] Example 2

[0069] Reference Figure 4 As shown, this embodiment provides a target discrimination system based on a moving trajectory. The system includes:

[0070] The zone boundary setting module 1 is used to determine the zone boundary based on the shape of the zone and to set the location information of the zone boundary;

[0071] The zone meshing module 2 is used to divide defense zones using square grids and assign a unique number and corresponding weight value to each grid.

[0072] Signal monitoring module 3 is used to detect target signals and record and continuously monitor the target when it is outside the defense zone;

[0073] Signal location determination module 4 is used to determine whether the target is within the defense zone based on the location information of the defense zone boundary;

[0074] The movement trajectory prediction module 5 is used to assign a defense zone identifier to the target when it crosses the defense zone boundary and enters the defense zone, determine the grid where the target is located, and predict the movement trajectory based on the target's location. The movement trajectory prediction module 5 includes:

[0075] The first processing submodule 51 is used to calculate the weight value of the target based on the weight value corresponding to the grid on the target's movement trajectory within the defense zone when the target moves within the defense zone, and to determine whether the target is a real target.

[0076] The second processing submodule 52 is used to mark the grid as an active grid when the target has not moved in the grid and the detection signal has disappeared, so that when the target reappears, the target can be directly assigned a defense zone identifier and enter the movement trajectory prediction.

[0077] The third processing submodule 53 is used to remove the target's defense zone identifier and switch to the outside-defense zone monitoring state when the target leaves its grid and moves to the outside of the defense zone.

[0078] In this embodiment, the first processing submodule 51 includes:

[0079] Effective prediction grid determination unit 511 is used to determine the grids adjacent to the target grid in the defense zone as effective prediction grids based on the grid where the target is located;

[0080] The weight value calculation unit 512 is used to accumulate the weight value of the target when the target moves to an adjacent grid, or to subtract the weight value of the target when the target moves to another grid outside the effective prediction grid.

[0081] The movement trajectory discrimination unit 513 is used to discriminate the calculated target weight value based on the target movement trajectory. If the target weight value is greater than or equal to the preset upper limit of the weight threshold, the target movement trajectory is judged to be real; or, if the target weight value is less than or equal to the preset lower limit of the weight threshold, the target movement trajectory is judged to be abnormal.

[0082] In this embodiment, the weight values ​​of the grid are set individually or uniformly.

[0083] In this embodiment, the size of the square grid is 2m × 2m.

[0084] The system includes a zone boundary setting module 1, used to determine the zone boundary based on the shape of the zone and set the location information of the zone boundary; a zone gridding module 2, used to divide the zone into square grids and assign a unique number and corresponding weight value to each grid; a signal monitoring module 3, used to detect target signals and record and continuously monitor the target when it is outside the zone; a signal position judgment module 4, used to determine whether the target is inside the zone based on the location information of the zone boundary; and a movement trajectory prediction module 5, used to assign a zone identifier to the target when it crosses the zone boundary and enters the zone, determine the grid where the target is located, and predict the movement trajectory based on the target's location. The movement trajectory prediction module 5 includes a first processing submodule 51, which calculates the weight value of the target based on the weight value corresponding to the grid on the target's movement trajectory within the defense zone when the target moves within the defense zone, and determines whether the target is a real target; a second processing submodule 52, which marks the grid as an active grid when the target does not move within its grid and the detection signal disappears, so that when the target reappears, it can be directly assigned a defense zone identifier and enter the movement trajectory prediction; and a third processing submodule 53, which removes the defense zone identifier of the target and switches to an outside-defense zone target monitoring state when the target exits from its grid to the outside of the defense zone.

[0085] This system can effectively distinguish between real and fake moving targets, eliminate false targets, and thus effectively identify the authenticity of targets, thereby improving the radar's ability to detect targets. For specific implementation details, please refer to the relevant description in Embodiment 1, which will not be elaborated here.

[0086] Example 3

[0087] This embodiment provides a radar device, which includes the target discrimination system based on the moving trajectory as described above.

[0088] The target discrimination system based on movement trajectory is based on target location information and gridded attribute information of defense zone. Therefore, it is applicable to a variety of radar equipment. This radar equipment can be combined with audio-visual equipment, video surveillance and other equipment. It can be used in various ways such as pole mounting and wall mounting. It can further improve the target recognition effect on the basis of radar detection accuracy.

[0089] In summary, this invention is applicable to a wide range of monitoring scenarios, such as border lines, water areas, and nature reserves. It can identify targets in a short time, continuously record target movement trajectories, and provide data support for subsequent evidence collection and incident handling.

[0090] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A target discrimination method based on movement trajectory, characterized in that, include: Step S1: Determine the boundary of the defense zone based on the shape of the defense zone, and set the location information of the defense zone boundary; Step S2: Divide the defense zone into square grids and assign a unique number and corresponding weight value to each grid; Step S3: Detect the target signal, determine whether the target is inside the defense zone based on the position information of the defense zone boundary. If the target is outside the defense zone, record and continuously monitor the target. If the target crosses the defense zone boundary and enters the defense zone, proceed to step S4. Step S4: Assign a defense zone identifier to the target, determine the grid in which the target is located, and predict the movement trajectory based on the target's location; Step S5: When the target moves within the defense zone, calculate the weight value of the target based on the weight value corresponding to the grid where the target's movement trajectory is located, and determine whether the target is a real target. Alternatively, when the target does not move within its grid and the detection signal disappears, mark the grid as an active grid so that when the target reappears, directly assign a defense zone identifier to the target and enter the movement trajectory prediction. Or, when the target exits from its grid to outside the defense zone, remove the target's defense zone identifier and switch to the outside target monitoring state. In step S5, when the target moves within the defense zone, a weight value is calculated for the target based on the weight value corresponding to the grid where the target's movement trajectory is located, and it is determined whether the target is a real target. Specifically, this includes: Step S51: Based on the grid where the target is located, determine the grids adjacent to that grid within the defense zone as valid prediction grids; Step S52: If the target moves to an adjacent grid, the weight value of the target is accumulated; if the target moves to another grid outside the effective prediction grid, the weight value of the target is subtracted. Step S53: Repeat steps S51 and S52 based on the target movement trajectory until the target weight value is greater than or equal to the preset upper limit of the weight threshold, then the target movement trajectory is determined to be real; or, if the target weight value is less than or equal to the preset lower limit of the weight threshold, then the target movement trajectory is determined to be abnormal.

2. The target discrimination method based on movement trajectory according to claim 1, characterized in that, In step S3, one or more targets outside the defense zone are continuously monitored.

3. The target discrimination method based on movement trajectory according to claim 1, characterized in that, The weight values ​​of the grid can be set individually or uniformly.

4. The target discrimination method based on movement trajectory according to claim 1, characterized in that, The square grid is 2m × 2m in size.

5. A target discrimination system based on a moving trajectory, characterized in that, The system includes: The zone boundary setting module is used to determine the zone boundary based on the shape of the zone and to set the location information of the zone boundary. The defense zone meshing module is used to divide the defense zones into square grids and assign a unique number and corresponding weight value to each grid. The signal monitoring module is used to detect target signals and record and continuously monitor the target when it is outside the defense zone; The signal location determination module is used to determine whether the target is within the defense zone based on the location information of the defense zone boundary. A movement trajectory prediction module is used to assign a defense zone identifier to a target when it crosses the defense zone boundary and enters the defense zone, determine the grid where the target is located, and predict its movement trajectory based on the target's location. The movement trajectory prediction module includes: The first processing submodule is used to calculate the weight value of the target based on the weight value corresponding to the grid where the target's movement trajectory is located when the target moves within the defense zone, and to determine whether the target is a real target. The second processing submodule is used to mark the grid as an active grid when the target has not moved and the detection signal has disappeared, so that when the target reappears, the target can be directly assigned a defense zone identifier and enter the movement trajectory prediction. The third processing submodule is used to remove the target's defense zone identifier and switch to the outside-defense zone monitoring state when the target leaves the grid where it is located and moves to the outside of the defense zone. The first processing submodule includes: An effective prediction grid determination unit is used to determine, based on the grid where the target is located, the grids adjacent to that grid within the defense zone as effective prediction grids; The weight value calculation unit is used to accumulate the weight value of the target when the target moves to an adjacent grid, or to subtract the weight value of the target when the target moves to another grid outside the effective prediction grid. The movement trajectory discrimination unit is used to discriminate the calculated target weight value based on the target's movement trajectory. If the target weight value is greater than or equal to the preset upper limit of the weight threshold, the target movement trajectory is judged to be real; or, if the target weight value is less than or equal to the preset lower limit of the weight threshold, the target movement trajectory is judged to be abnormal.

6. The target discrimination system based on moving trajectory according to claim 5, characterized in that, The weight values ​​of the grid can be set individually or uniformly.

7. The target discrimination system based on moving trajectory according to claim 5, characterized in that, The square grid is 2m × 2m in size.

8. A radar device, characterized in that, The radar device includes a target discrimination system based on a moving trajectory as described in any one of claims 5-7.

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