Radar environment false alarm elimination method and device, storage medium and product

Abstract

The invention discloses a radar environment false alarm elimination method and device, a storage medium and a product, and relates to the field of radars. The method comprises the following steps: creating a raster data structure chart; acquiring point cloud data of all targets in a radar detection area; calculating the grid position of each target point in the grid data structure chart, and storing the energy signal-to-noise ratio and the angle signal-to-noise ratio of each target point to the corresponding grid position; repeating the steps of obtaining the point cloud data, calculating the grid position of each target point in the grid data structure diagram and storing the energy signal-to-noise ratio and the angle signal-to-noise ratio of each target point until the set time is reached; calculating the confidence coefficient of the corresponding grid according to the energy signal-to-noise ratio and the angle signal-to-noise ratio of each grid in the grid data structure chart; and judging whether the target point is an environment false alarm target or not according to the confidence of each grid. According to the method, automatic elimination of the environment false alarm target is realized, manual elimination is not needed, and the false alarm elimination efficiency is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the field of radar technology, and in particular relates to a radar environment false alarm elimination method, equipment, storage medium and product. Background Art

[0002] Millimeter wave radar transmits multiple cycles of frequency modulated continuous wave (FMCW) signals, each frequency sweep cycle is T chirp , the distance and radial velocity can be measured simultaneously for each target in a multi-target scene. The emitted waveform is as follows Figure 1 As shown, where f 0 represents the radar starting frequency, and B represents the signal bandwidth.

[0003] The transmitted signal is reflected by the target to obtain the echo signal. After the echo signal is mixed with the transmitted signal, the frequency containing f B The baseband signal can be processed by two-dimensional fast Fourier transform to obtain the frequency of the difference frequency signal f B and Doppler frequency f D The target distance R and target speed V can be calculated by the following formulas:

[0004]

[0005] Where c is the speed of light, T chirp represents the repetition period, B represents the signal bandwidth, λ represents the wavelength, and τ represents the time difference between the transmitted signal and the received signal.

[0006] During the target detection process of radar, the radar transmitter will emit electromagnetic wave signals with a certain bandwidth into space. When these electromagnetic wave signals reach the detected target, the target will scatter the signals in all directions of space, and part of the signals will return directly to the radar receiver along the path of the transmitted signal. The radar receiver will extract the target's distance, speed, direction and other information through signal processing methods based on the wave path difference between the transmitted signal and the received signal.

[0007] However, if there are non-rigid objects such as trees and grass in the target environment, and there is wind in the environment, these non-rigid objects will sway with the wind, and after the signal returns to the radar receiver, they will also be judged as moving targets. Figure 2 The moving targets generated by these shaking will cause the system to generate false alarms, and even interfere with the detection of real targets, causing the radar to misjudge, seriously affecting the target tracking performance of the radar system.

[0008] Therefore, it is very necessary to eliminate environmental false alarms. However, environmental false alarms are objective phenomena based on radar principles and cannot be eliminated by radar principles. In order to reduce such false alarms, radar systems usually require that such non-rigid targets should not exist in the monitoring scene as much as possible, and eliminate such short-range fast-moving or short-range back-and-forth moving targets according to the target motion trajectory. However, these methods can only eliminate some environmental false alarms to a limited extent, and also reduce the radar's reaction speed to the target and the monitoring of its own micro-moving targets. The increasing demand for target display speed and target accuracy also makes such methods difficult to use.

[0009] Therefore, only by eliminating such targets after target detection can we more effectively eliminate environmental false alarms without affecting the detection of real targets. At present, the local area of ​​radar detection is usually manually zoned according to the actual environment, and all targets outside the zone are eliminated to suppress the generation of environmental false alarms. This method is difficult to implement manually when there are many static environmental targets in the environment, and the zones for each scene are different and need to be adjusted, which is labor-intensive. At the same time, the error range of manual zone drawing is large, and it is easy to make fewer draws, resulting in failure to completely suppress false alarms, or make more draws, resulting in suppression of real targets. Summary of the invention

[0010] The purpose of the present invention is to provide an environmental false alarm elimination method, device, storage medium and product to solve the problems that the traditional manual zone drawing method is difficult to implement, has a large workload, is inefficient, and is prone to missed reports or false alarms.

[0011] The present invention solves the above technical problems through the following technical solutions: a method for eliminating false alarms in radar environments, comprising:

[0012] Create a raster data structure diagram based on the radar detection range;

[0013] Obtaining point cloud data of all targets within the radar detection area; wherein the point cloud data includes the position, energy signal-to-noise ratio and angle signal-to-noise ratio of each target point;

[0014] Calculate the grid position of the corresponding target point in the grid data structure diagram according to the position of each target point, the radar detection range and the grid size of the grid data structure diagram;

[0015] The energy signal-to-noise ratio and the angle signal-to-noise ratio of each target point are stored in the grid position of the corresponding target point in the grid data structure diagram;

[0016] Repeat the steps of acquiring point cloud data, calculating the grid position of each target point in the grid data structure diagram, and storing the energy signal-to-noise ratio and the angle signal-to-noise ratio of each target point until a set time is reached;

[0017] Calculating the confidence of the corresponding grid according to the energy signal-to-noise ratio and the angle signal-to-noise ratio of each grid in the grid data structure diagram;

[0018] According to the confidence of each grid, it is judged whether the target point corresponding to the grid is an environmental false alarm target; if so, it is eliminated.

[0019] Furthermore, the specific calculation formula for the grid position of each target point in the grid data structure diagram is:

[0020]

[0021] Among them, Loc i Indicates the grid position of the i-th target point in the grid data structure diagram, (x i ,y i ) represents the position of the i-th target point, (x min ,x max ) represents the detection range of the radar in the horizontal direction, y min It represents the minimum value of the radar's detection range in the vertical direction, and w represents the width of the grid in the grid data structure diagram.

[0022] Furthermore, the specific calculation formula for the confidence of each grid is:

[0023]

[0024] Among them, R j represents the confidence of the jth grid, H represents that the signal energy distribution curve of the jth grid is greater than X c And except for the noise energy distribution curve of the jth grid greater than X c FA indicates that the noise energy distribution curve of the jth grid is greater than X c Part, X c represents the intersection point of the noise energy distribution and signal energy distribution of the jth grid, f 1 represents the weight value of the energy signal-to-noise ratio of the jth grid, f 2 represents the weight value of the angle signal-to-noise ratio of the jth grid, E Sj represents the energy signal-to-noise ratio of the jth grid, E Nj represents the angle signal-to-noise ratio of the jth grid, Var represents the standard deviation of radar noise, and f 1 +f 2 =1.

[0025] Furthermore, the weight value f of the energy signal-to-noise ratio 1 The weight value f is smaller than the angle signal-to-noise ratio 2 .

[0026] Furthermore, the weight value f of the energy signal-to-noise ratio1 Set to 0.3, the weight value of the angle signal-to-noise ratio f 2 Set to 0.7.

[0027] Further, judging whether the target point corresponding to each grid is an environmental false alarm target according to the confidence of each grid specifically includes:

[0028] The false alarm degree index of the corresponding target point is calculated according to the confidence of each grid. The specific calculation formula is:

[0029]

[0030] Among them, P j Represents the false alarm degree index of the target point corresponding to the jth grid, R j Represents the confidence of the jth grid;

[0031] It is determined whether the false alarm degree index of the target point exceeds a set threshold. If so, the target point is an environmental false alarm target and is removed.

[0032] Furthermore, in a strong wind detection environment, the elimination method further includes eliminating target points of surrounding grids of the grid corresponding to the environmental false alarm target.

[0033] Based on the same concept, the present invention also provides an electronic device, including a memory, a processor, and a computer program / instruction stored in the memory, wherein the processor executes the computer program / instruction to implement the radar environment false alarm elimination method as described above.

[0034] Based on the same concept, the present invention also provides a computer-readable storage medium on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the above-mentioned radar environment false alarm elimination method is implemented.

[0035] Based on the same concept, the present invention also provides a computer program product, including a computer program / instruction, which implements the above-mentioned radar environment false alarm elimination method when executed by a processor.

[0036] Beneficial Effects

[0037] Compared with the prior art, the advantages of the present invention are:

[0038] The present invention constructs a map of the radar detection environment according to point cloud data in the radar detection area, and then judges and eliminates environmental false alarm targets according to the constructed environment map-grid data structure map, thereby realizing automatic elimination of environmental false alarm targets without manual elimination of environmental false alarm targets, and greatly improving false alarm elimination efficiency; the present invention can lock environmental false alarm targets more accurately and quickly, eliminate environmental false alarm targets while ensuring real targets, improve false alarm elimination accuracy, improve missed reports or false alarm problems, and enhance the overall tracking effect of the radar, so that the radar can have faster response capabilities and more accurate target positioning capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only one embodiment of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 is the FMCW signal sequence in the background technology of the present invention;

[0041] Figure 2 It is a schematic diagram of the generation of environmental false alarm targets in the background technology of the present invention;

[0042] Figure 3 is a flow chart of a method for eliminating false alarms in a radar environment according to an embodiment of the present invention;

[0043] Figure 4 is a schematic diagram of the position of point cloud data in a rectangular coordinate system in an embodiment of the present invention;

[0044] Figure 5 is an energy distribution diagram of noise and signal in an embodiment of the present invention;

[0045] Figure 6 1 is a grid data structure diagram after calculating the false alarm degree index in an embodiment of the present invention; wherein the horizontal axis and the vertical axis both represent the number of grids. DETAILED DESCRIPTION

[0046] The following is a clear and complete description of the technical solutions in the present invention 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.

[0047] The technical solution of the present application is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0048] Example 1

[0049] Figure 3 The flowchart of the method for eliminating false alarms in radar environment provided by the present invention is shown as follows: Figure 3 As shown, the method for eliminating environmental false alarms comprises the following steps:

[0050] Step 1: Create a raster data structure diagram based on the radar detection range.

[0051] Assume that the detection range of the radar in the horizontal direction is (x min ,x max ), the vertical detection range of the radar is (y min ,y max ), determine the size w of each grid in the grid data structure diagram according to the accuracy requirements, that is, the width or side length of each grid, and create a grid with a size of (x min -x max ) × (and min -and max ) Grid data structure diagram. For example, the detection range of the radar in the horizontal direction is

[0052] ww

[0053] (-30m, 30m), the vertical detection range of the radar is (0, 250m), the width or side length of each grid is 0.25m, thus constructing a 240×1000 grid data structure diagram, such as Figure 6 As shown, 240 is the number of horizontal grids and 1000 is the number of vertical grids.

[0054] Step 2: Under the condition that there are no external stationary targets that do not belong to the radar detection environment, obtain the point cloud data of all targets in the radar detection area of ​​the current frame.

[0055] The point cloud data includes the position, energy signal-to-noise ratio and angle signal-to-noise ratio of each target point (i.e., target). The position, energy signal-to-noise ratio and angle signal-to-noise ratio of the target point can be obtained during radar target detection and angle measurement. The target points include moving targets and stationary targets. A rectangular coordinate system is constructed with the radar as the origin. The position of each target point in the rectangular coordinate system is as follows: Figure 4 As shown, the horizontal axis represents the horizontal distance of the target point, and the vertical axis represents the vertical distance of the target point. Figure 4 There are 3478 target points or objectives in total.

[0056] Step 3: Calculate the grid position of the corresponding target point in the grid data structure diagram according to the position of each target point, the radar detection range and the grid size of the grid data structure diagram.

[0057] In order to assign each target point in the point cloud data to the grid of the grid data structure diagram, it is necessary to calculate the grid position of each target point in the grid data structure diagram. In a specific embodiment of the present invention, the specific calculation formula for the grid position of each target point in the grid data structure diagram is:

[0058]

[0059] Among them, Loc i Indicates the grid position of the i-th target point in the grid data structure diagram, (x i ,y i ) represents the position of the i-th target point, (x min ,x max ) represents the detection range of the radar in the horizontal direction, y min It represents the minimum value of the radar's detection range in the vertical direction, and w represents the width of the grid in the grid data structure diagram.

[0060] For example, for a 240×1000 grid data structure diagram, if the LOC value is 240, the grid position of the target point in the grid data structure diagram is the 1st row and 240th column; if the LOC value is 241, the grid position of the target point in the grid data structure diagram is the 2nd row and 1st column.

[0061] Step 4: Store the energy signal-to-noise ratio and angle signal-to-noise ratio of each target point to the grid position of the corresponding target point in the grid data structure diagram.

[0062] Based on the grid position of each target point in the grid data structure diagram calculated in step 3, the energy signal-to-noise ratio and angle signal-to-noise ratio of each target point are stored in the corresponding grid.

[0063] Step 5: Determine whether the set time has been reached. If so, proceed to step 6; otherwise, proceed to step 2 according to the radar detection cycle to achieve the accumulation of point cloud data in the grid data structure diagram.

[0064] Since the targets existing in the radar detection environment will be accumulated, and the mis-entered moving targets will not be accumulated because they will not exist continuously in a certain position, the interval radar detection cycle and the accumulation operation of point cloud data can reduce the influence of mis-detected targets and mis-entered moving targets on the confidence of the grid data structure diagram. In this embodiment, the radar detection cycle is 0.1s (i.e., detection once every 0.1s), accumulation is once every 10 frames, i.e., accumulation is once every 1s, and the set time is 40s, i.e., the confidence of the grid is calculated after 40 accumulations. The longer the accumulation time (i.e., the more times steps 2 to 4 are repeated), the higher the confidence of the calculation.

[0065] Step 6: Calculate the confidence of the corresponding grid according to the energy signal-to-noise ratio and angle signal-to-noise ratio of each grid in the grid data structure diagram.

[0066] Under normal circumstances, it is believed that the environmental noise energy distribution conforms to the normal distribution, the signal energy is a fixed value, and the signal energy distribution is the fixed energy plus the noise energy distribution, so the signal energy distribution also conforms to the normal distribution. The normal distribution formula is as follows:

[0067]

[0068] Among them, μ represents the overall mean of energy, σ represents the overall standard deviation of energy, and X represents energy; in the signal field, μ represents energy and σ represents the fluctuation of noise.

[0069] The signal energy of the target point (corresponding to the grid) must be greater than the noise energy, so the energy distribution of the noise and signal at the target point is as follows: Figure 5 shown. Figure 5 In the figure, the left side is the noise energy distribution of the target point, and the right side is the signal energy distribution of the target point. The intersection of the noise energy distribution and the signal energy distribution of the target point is X c , X c It is obtained by normalizing the weighted sum of the energy signal-to-noise ratio and the angle signal-to-noise ratio of the target point; M means that the signal energy distribution curve of the target point is less than X c The part (i.e., missed alarm area) indicates that the target is a real target but is judged as a false alarm target; FA indicates that the noise energy distribution curve of the target point is greater than X c The part (i.e., false alarm area) indicates that the target is a false alarm target but is determined to be a real target; H indicates that the signal energy distribution curve of the target point is greater than X c And the energy distribution curve of the noise removal is greater than X c The part (i.e., the hit area) indicates that the target is correctly identified as a real target; CR indicates that the noise energy distribution curve of the target point is less than X c And remove the signal energy distribution curve less than X cThe part (i.e., the correct rejection area) is the case where the target is correctly judged as a false alarm target. c The specific calculation formula of (the normalized value of the weighted sum of energy signal-to-noise ratio and angle signal-to-noise ratio) is:

[0070]

[0071] Among them, f 1 represents the weight value of the energy signal-to-noise ratio of the jth grid, f 2 represents the weight value of the angle signal-to-noise ratio of the jth grid, E Sj represents the energy signal-to-noise ratio of the jth grid (converted from the energy value and the background noise value), E Nj represents the angle signal-to-noise ratio of the jth grid, Var represents the standard deviation of radar noise, and f 1 +f 2 =1 and f 1 <f 2 Since the difference between the angle signal-to-noise ratio of the environmental false alarm target and the real target is more obvious, the weight value of the energy signal-to-noise ratio is f 1 If the setting is too small, the angle signal-to-noise ratio f 2 The weight value of the energy signal-to-noise ratio is set too large. 1 Set to 0.3, the weight value of the angle signal-to-noise ratio f 2 The radar noise variance in this embodiment is 3 dB, so the standard deviation Var of the radar noise is set to 1.7.

[0072] According to the normalized value X of the weighted sum of energy signal-to-noise ratio and angle signal-to-noise ratio c ,right Figure 5 By integrating the normal distribution of , we can get the confidence of each grid. The specific calculation formula is:

[0073]

[0074] Among them, R j Represents the confidence of the j-th grid. represents the probability that the target is the real target, It represents the total probability that the target is a true target and the target is a false alarm target. The ratio of the two is the confidence that the target is a true target.

[0075] Step 7: According to the confidence of each grid, determine whether the target point corresponding to the grid is an environmental false alarm target; if so, remove it.

[0076] In a specific embodiment of the present invention, judging whether a target point corresponding to a grid is an environmental false alarm target according to the confidence of each grid specifically includes:

[0077] Step 7.1: Calculate the false alarm index of the corresponding target point according to the confidence level of each grid. The specific calculation formula is:

[0078]

[0079] Among them, P j Represents the false alarm degree index of the target point corresponding to the jth grid, R j Represents the confidence of the jth grid;

[0080] Step 7.2: Determine whether the false alarm degree index of the target point exceeds the set threshold. If so, the target point is an environmental false alarm target and is removed (normal removal).

[0081] The threshold is determined based on the false alarm degree index of the grid with environmental false alarm targets and the false alarm degree index of the grid without environmental false alarms after radar actual measurement. In this embodiment, the threshold is set to 1000.

[0082] Compared with the decimal confidence level, the false alarm degree index is better used to determine whether it is an environmental false alarm target. Figure 6 The figure shows the grid data structure diagram after calculating the false alarm degree index, that is, each grid unit represents the false alarm degree index of the corresponding target point. The higher the false alarm degree index (such as the yellow area), the greater the false alarm probability; the lower the false alarm degree index (such as the blue area), the smaller the false alarm probability.

[0083] Step 8: In a high wind detection environment, target points of the surrounding grids of the grid corresponding to the environmental false alarm target are eliminated (i.e., expansion elimination).

[0084] Since most of the environmental false alarm targets are non-rigid objects, they may have large displacements under conditions such as strong winds. If the grid unit is set relatively small (that is, the size of the grid unit is small), the environmental false alarm targets may enter the surrounding grid units. Therefore, in a strong wind detection environment, not only the target points whose false alarm degree index exceeds the set threshold are deleted, but also the target points of the grids around the target points are deleted. According to the strong wind level and the size of the grid unit, the range of the target points to be deleted from the surrounding grids is determined. Expansion elimination can deal with false alarm targets generated in extreme environments (such as strong wind environments). Expansion elimination will cause the monitoring targets that overlap with the stationary target position to be unable to be detected, but it has a stronger ability to deal with false alarms and is suitable for environments where stationary target areas are not considered.

[0085] Example 2

[0086] An embodiment of the present invention further provides an electronic device, which includes: a memory, a processor, and a computer program / instruction stored in the memory, and the processor executes the computer program / instruction to implement the radar environment false alarm elimination method in the embodiment of the present application.

[0087] Although not shown, the electronic device includes a processor, which can perform various appropriate operations and processes according to the program and / or data stored in the read-only memory (ROM) or the program and / or data loaded from the storage portion into the random access memory (RAM). The processor can be a multi-core processor, or it can include multiple processors. In some embodiments, the processor can include a general main processor and one or more special coprocessors, such as a central processing unit, a graphics processing unit (GPU), a neural network processor (NPU), a digital signal processor (DSP), etc. In RAM, various programs and data required for device operation are also stored. The processor, ROM and RAM are connected to each other via a bus. The input / output (I / O) interface is also connected to the bus.

[0088] The processor and memory are used together to execute the program / instructions stored in the memory. When the program / instructions are executed by the computer, the methods, steps or functions described in the above embodiments can be implemented.

[0089] Although not shown, an embodiment of the present invention further provides a computer-readable storage medium on which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the radar environment false alarm elimination method in the embodiment of the present application is implemented.

[0090] Readable storage media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0091] Although not shown, an embodiment of the present invention further provides a computer program product, including: a computer program / instruction, which, when executed by a processor, implements the radar environment false alarm elimination method in the embodiment of the present application.

[0092] What is disclosed above is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or modifications within the technical scope disclosed in the present invention, which should be covered within the protection scope of the present invention.

Claims

1. A method for eliminating false alarms in a radar environment, characterized in that: The elimination method includes: Create a raster data structure diagram based on the radar detection range; Obtaining point cloud data of all targets within the radar detection area; wherein the point cloud data includes the position, energy signal-to-noise ratio and angle signal-to-noise ratio of each target point; Calculate the grid position of the corresponding target point in the grid data structure diagram according to the position of each target point, the radar detection range and the grid size of the grid data structure diagram; The energy signal-to-noise ratio and the angle signal-to-noise ratio of each target point are stored in the grid position of the corresponding target point in the grid data structure diagram; Repeat the steps of acquiring point cloud data, calculating the grid position of each target point in the grid data structure diagram, and storing the energy signal-to-noise ratio and the angle signal-to-noise ratio of each target point until a set time is reached; Calculating the confidence of the corresponding grid according to the energy signal-to-noise ratio and the angle signal-to-noise ratio of each grid in the grid data structure diagram; According to the confidence of each grid, it is judged whether the target point corresponding to the grid is an environmental false alarm target; if so, it is eliminated.

2. The method for eliminating false alarms in radar environment according to claim 1, characterized in that: The specific calculation formula for the grid position of each target point in the grid data structure diagram is: Among them, Loc i Indicates the grid position of the i-th target point in the grid data structure diagram, (x i ,y i ) represents the position of the i-th target point, (x min ,x max ) represents the detection range of the radar in the horizontal direction, y min It represents the minimum value of the radar's detection range in the vertical direction, and w represents the width of the grid in the grid data structure diagram.

3. The method for eliminating false alarms in radar environment according to claim 1, characterized in that: The specific calculation formula for the confidence of each grid is: Among them, R j represents the confidence of the jth grid, H represents that the signal energy distribution curve of the jth grid is greater than X c And except for the noise energy distribution curve of the jth grid greater than X c FA indicates that the noise energy distribution curve of the jth grid is greater than X c Part, X c represents the intersection of the noise energy distribution and the signal energy distribution of the j-th grid, f1 represents the weight value of the energy signal-to-noise ratio of the j-th grid, f2 represents the weight value of the angle signal-to-noise ratio of the j-th grid, E Sj represents the energy signal-to-noise ratio of the jth grid, E Nj represents the angular signal-to-noise ratio of the jth grid, Var represents the standard deviation of radar noise, and f1+f2=1.

4. The method for eliminating false alarms in radar environment according to claim 3, characterized in that: The weight value f1 of the energy signal-to-noise ratio is smaller than the weight value f2 of the angle signal-to-noise ratio.

5. The method for eliminating false alarms in radar environment according to claim 3, characterized in that: The weight value f1 of the energy signal-to-noise ratio is set to 0.3, and the weight value f2 of the angle signal-to-noise ratio is set to 0.

7.

6. The method for eliminating false alarms in radar environment according to claim 1, characterized in that: Judging whether the target point corresponding to each grid is an environmental false alarm target according to the confidence of each grid, specifically includes: The false alarm degree index of the corresponding target point is calculated according to the confidence of each grid. The specific calculation formula is: Among them, P j Represents the false alarm degree index of the target point corresponding to the jth grid, R j Represents the confidence of the jth grid; It is determined whether the false alarm degree index of the target point exceeds a set threshold. If so, the target point is an environmental false alarm target and is removed.

7. The method for eliminating false alarms in radar environment according to any one of claims 1 to 6, characterized in that: In a strong wind detection environment, the elimination method further includes eliminating target points of surrounding grids of the grid corresponding to the environmental false alarm target.

8. An electronic device comprising a memory, a processor, and a computer program / instruction stored in the memory, wherein the processor executes the computer program / instruction to implement the radar environment false alarm elimination method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program / instruction stored thereon, wherein the computer program / instruction, when executed by a processor, implements the radar environment false alarm elimination method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program / instruction, wherein when the computer program / instruction is executed by a processor, the method for eliminating false alarms in a radar environment as claimed in any one of claims 1 to 7 is implemented.

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