Method and device for eliminating unintentional track based on prior track information

Abstract

The application provides an unintentional interference point track elimination method and device based on prior point track information, and relates to the technical field of radar target detection. The method comprises the following steps: S1, acquiring point track data of multiple periods under the same scene to generate a point track distribution graph; S2, performing grid processing on the point track distribution graph to generate a two-dimensional grid graph; S3, determining the distribution position of interference point tracks along the bearing direction of the two-dimensional grid graph by using a sliding window detection method to generate a two-dimensional mask; and S4, performing mask processing on the two-dimensional grid graph by using the two-dimensional mask, filtering out the interference point tracks by using the two-dimensional grid graph after mask processing, and generating a new point track graph. The application can accurately and effectively shield the area where the interference point tracks are located, without causing interference to the effective point tracks of targets, so that the generation of interference tracks is greatly reduced.

Description

Technical Field

[0001] This invention relates to the field of radar target detection technology, and in particular to a method and apparatus for removing unintentional interference points based on prior point information. Background Technology

[0002] Currently, when radar detects low-lying, slow-moving targets on the ground, numerous strong scattering objects on the ground, such as wind turbines, barbed wire fences, and utility poles, are detected due to their localized movement, forming a large number of interference points in the target tracking map. These interference points are dense, widely distributed, and easily cause the formation of interference tracks, seriously affecting the effective detection and tracking of targets. Therefore, how to eliminate such points to the greatest extent possible has become a difficult problem in radar target detection.

[0003] Common interference suppression methods include spatiotemporal adaptive processing, moving target detection, and point classification. Spatiotemporal adaptive processing simultaneously handles adaptive arrays in both the spatial and temporal domains. Moving target detection is performed directly on the range-Doppler matrix data, performing spectral analysis on the slow time series of each range cell to remove the zero frequencies corresponding to clutter. However, both of these methods are designed for environments where stationary targets tend to concentrate at zero frequencies. When complex ground features and interference exist in the environment, simply removing zero frequencies cannot completely suppress clutter. Point classification methods commonly include unsupervised clustering and supervised classification. Unsupervised clustering methods lack prior knowledge and often rely on location information for clustering, making it difficult to remove interfering points mixed within the target area. Supervised classification, on the other hand, requires significant manpower for data annotation. Summary of the Invention

[0004] In view of the above problems, the present invention provides a method and apparatus for removing unintentional interference marks based on prior mark information.

[0005] This invention provides a method for removing unintentional interference points based on prior point information, comprising: step S1, acquiring multi-period point data in the same scene and generating a point distribution map; step S2, performing rasterization processing on the point distribution map to generate a two-dimensional raster map; step S3, determining the distribution location of interference points along the orientation of the two-dimensional raster map using a sliding window detection method and generating a two-dimensional mask; step S4, using the two-dimensional mask to perform masking processing on the two-dimensional raster map, and using the masked two-dimensional raster map to filter out the interference points and generate a new point map.

[0006] According to an embodiment of the present invention, step S1 specifically includes: step S11, acquiring multi-period point data of the same scene by ground-based radar, wherein the point data includes azimuth angle and distance information; step S12, superimposing and displaying the multi-period point data, and drawing the point distribution map in the polar coordinate system of distance and azimuth angle.

[0007] According to an embodiment of the present invention, step S2 specifically includes: dividing the point distribution map into grids according to a preset azimuth sampling interval and distance sampling interval to generate the two-dimensional grid map.

[0008] According to an embodiment of the present invention, the azimuth sampling interval and the range sampling interval are both selected based on the angular accuracy and ranging resolution of the ground-based radar.

[0009] According to an embodiment of the present invention, dividing the dot distribution map into grids includes projecting the dot data onto a two-dimensional grid map according to the following formula:

[0010]

[0011] In the formula, I(x,y) is a two-dimensional matrix of a two-dimensional raster image; tar_point is the set of coordinates of the points after quantization according to the sampling interval, consisting of azimuth angle coordinates x and distance coordinates y.

[0012] According to an embodiment of the present invention, step S3 specifically includes: step S31, calculating the pixel density of interference points in each sliding window by means of sliding window detection along the orientation of the two-dimensional grid; step S32, setting a detection threshold, determining whether the pixel density in each sliding window is greater than the detection threshold, if so, the pixel in the sliding window is determined to be unintentional interference from the ground environment, and the mask value at the corresponding position is set to 0; otherwise, the mask value at the corresponding position is set to 1; step S33, repeating the above steps S31 to S32, generating the two-dimensional mask by detecting each distance gate sliding window.

[0013] According to an embodiment of the present invention, in step S31, the pixel density of interfering dots within each sliding window is calculated according to the following formula:

[0014]

[0015] In the formula, N is the preset azimuth sliding window length; ρx, y Let N be the pixel density of interfering points within a sliding window of size N; I(x, y) is a two-dimensional matrix of a two-dimensional raster image, containing the azimuth coordinate x and the distance coordinate y.

[0016] According to an embodiment of the present invention, the two-dimensional mask and the two-dimensional grid image after mask processing are calculated according to the following formula:

[0017]

[0018] I′(x,y)=mask(x,y)·I(x,y)

[0019] In the formula, mask(·) represents a two-dimensional mask, which is a two-dimensional matrix of the same size as I(x,y); ρ0 is the detection threshold; and I′(x,y) is the two-dimensional raster image after masking.

[0020] Another aspect of the present invention provides an unintentional interference mark removal device based on prior mark information, comprising: a mark acquisition module for acquiring multi-period mark data in the same scene and generating a mark distribution map; a rasterization module for rasterizing the mark distribution map to generate a two-dimensional raster map; a mask generation module for determining the distribution position of interference marks along the orientation of the two-dimensional raster map using a sliding window detection method and generating a two-dimensional mask; and an interference filtering module for using the two-dimensional mask to perform mask processing on the two-dimensional raster map, filtering out the interference marks using the masked two-dimensional raster map, and generating a new mark map.

[0021] Compared with the prior art, the method and apparatus for removing unintentional interference marks based on prior mark information provided by the present invention have at least the following beneficial effects:

[0022] (1) It can accurately and effectively shield the area where the interference points are located without interfering with the effective points of the target, thereby greatly reducing the generation of interference tracks;

[0023] (2) Finding interfering linear points by using an azimuth sliding window is more effective than methods such as line detection and can simplify calculations;

[0024] (3) By using a linear sliding window to eliminate interference points, linearly distributed points can be accurately removed. Moving targets have complex movements, and their points rarely move only along the azimuth direction while remaining unchanged in the distance direction. Therefore, this method results in less loss of effective moving target points.

[0025] (4) This method is simple and effective for unintentional interference points on linear ground, with good suppression effect, wide adaptability and good robustness. Attached Figure Description

[0026] The above and other objects, features and advantages of the present invention will become more apparent from the following description of embodiments of the invention with reference to the accompanying drawings, in which:

[0027] Figure 1 A flowchart illustrating an unintentional interference mark removal method based on prior mark information according to an embodiment of the present invention is shown.

[0028] Figure 2 A flowchart illustrating the process of generating a dot distribution map according to an embodiment of the present invention is shown schematically.

[0029] Figure 3The flowchart illustrating the interference point determination and two-dimensional mask generation process according to an embodiment of the present invention is shown in the schematic diagram.

[0030] Figure 4 A dot distribution map drawn according to an exemplary embodiment of the present invention is illustrated schematically;

[0031] Figure 5 A two-dimensional grid diagram corresponding to an exemplary embodiment of the present invention is illustrated schematically;

[0032] Figure 6 This illustration schematically shows a two-dimensional mask generated according to an exemplary embodiment of the present invention;

[0033] Figure 7 The diagram schematically illustrates a two-dimensional grid image after masking according to an exemplary embodiment of the present invention;

[0034] Figure 8 The illustration schematically shows a new dot pattern after filtering out interfering dots according to an exemplary embodiment of the present invention;

[0035] Figure 9 A block diagram of an unintentional interference mark removal device based on prior mark information according to an embodiment of the present invention is shown schematically. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0037] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0038] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0039] This invention analyzes the distribution characteristics of common strong scattering objects such as wind turbine towers, wire mesh, and utility poles. Based on the obvious linear distribution characteristics of the interfering points after multi-period superposition, a method is proposed to remove interfering scattering points by generating a mask from the point map.

[0040] Figure 1 The flowchart illustrates a method for removing unintentional interference dots based on prior dot information according to an embodiment of the present invention.

[0041] like Figure 1 As shown, the method for removing unintentional interference marks based on prior mark information according to this embodiment may include steps S1 to S4.

[0042] First, in step S1, multi-period spot data under the same scene is acquired to generate a spot distribution map.

[0043] Figure 2 A flowchart illustrating the point distribution map generation process according to an embodiment of the present invention is shown schematically. Figure 2 As shown in the embodiment of the present invention, step S1 specifically includes steps S11 to S112.

[0044] Step S11: The ground-based radar acquires multi-cycle point data in the same scene. The point data includes azimuth angle and distance information.

[0045] Step S12: Overlay and display the point data from multiple periods, and draw the point distribution map in the polar coordinate system of distance and azimuth.

[0046] Therefore, the point data acquired by ground-based radar, which includes the azimuth and distance information of the points, is used to draw a multi-period point distribution map of the surrounding environment in a polar coordinate system.

[0047] Secondly, in step S2, the point distribution map is rasterized to generate a two-dimensional raster map.

[0048] This step is the image rasterization process. Based on the distribution characteristics of the dots, the dot distribution map is rasterized in polar coordinates. The raster is divided based on the distribution pattern of the dots, and a corresponding two-dimensional raster map is established.

[0049] In this embodiment of the invention, the point distribution map is divided into grids according to the preset azimuth sampling interval and range sampling interval to generate a two-dimensional grid map.

[0050] Preferably, both the azimuth sampling interval and the range sampling interval are selected based on the angular accuracy and range resolution of the ground-based radar. Therefore, based on the maximum azimuth angle and range range of the ground-based radar's measured data, the number of pixels occupied by the generated two-dimensional grid image in the azimuth and range directions is determined.

[0051] Specifically, each point data is projected onto a two-dimensional raster image according to the two image sampling intervals mentioned above. If there are one or more points, the pixel at that location is filled with 255; otherwise, it is filled with 0, as shown in the following formula:

[0052]

[0053] In the formula, I(x, y) is a two-dimensional matrix of a two-dimensional raster image; tar_point is the set of coordinates of the points after quantization according to the sampling interval, consisting of azimuth coordinates x and distance coordinates y.

[0054] Next, in step S3, along the orientation of the two-dimensional grid, the distribution location of the interference points is determined by the sliding window detection method, and a two-dimensional mask is generated.

[0055] Figure 3 The flowchart illustrating the interference point determination and two-dimensional mask generation process according to an embodiment of the present invention is shown in the illustration.

[0056] Due to the movement patterns of interfering ground features, after angle measurement, they generally occupy multiple pixels in terms of azimuth angle, but regularly occupy a few pixels in terms of distance. This results in white discrete points distributed linearly in the two-dimensional grid image I(x,y). Taking advantage of this characteristic, this embodiment of the invention uses a sliding window detection method along the azimuth angle to determine the distribution location of the interfering point traces.

[0057] like Figure 3 As shown, in this embodiment of the invention, step S3 specifically includes steps S31 to S33.

[0058] Step S31: Along the orientation of the two-dimensional raster image, calculate the pixel density of interfering points within each sliding window using the sliding window detection method.

[0059] This step involves interference detection and localization. Specifically, for each azimuth at a sliding window located at (x, y), the pixel density of interference points within that window is calculated using the following formula:

[0060]

[0061] In the formula, N is the preset azimuth sliding window length; ρ x，y Let N be the pixel density of interfering points within a sliding window of size N; I(x, y) is a two-dimensional matrix of a two-dimensional raster image, containing the azimuth coordinate x and the distance coordinate y.

[0062] For example, N = 50 can be selected based on the distribution density of the interference dots.

[0063] Step S32: Set a detection threshold and determine whether the pixel density in each sliding window is greater than the detection threshold. If so, the pixel in the sliding window is determined to be unintentional interference from the ground environment, and the mask value at the corresponding position is set to 0; otherwise, the mask value at the corresponding position is set to 1.

[0064] If the detection threshold is denoted as ρθ, then if there is a pixel density ρx of interfering traces within the sliding window at any position (x, y), y If ρ > 0, the pixel in the sliding window is determined to be an unintentional interference from the ground environment, and the mask value at the corresponding position is set to 0; otherwise, the mask value at the corresponding position is set to 1.

[0065] For example, based on the distribution characteristics of the interference points, ρ0 = 0.4 can be selected according to the actual situation.

[0066] Step S33: Repeat steps S31 to S32 above to generate a two-dimensional mask by detecting each sliding window at a distance.

[0067] A two-dimensional mask can be generated by detecting each sliding door and window at a distance.

[0068] Finally, in step S4, a two-dimensional mask is used to mask the two-dimensional grid image, and the masked two-dimensional grid image is used to filter out interfering dots and generate a new dot map.

[0069] In this embodiment of the invention, the two-dimensional mask and the two-dimensional raster image after masking are calculated according to the following formula:

[0070]

[0071] I′(x,y)=mask(x,y)·I(x,y)

[0072] In the formula, mask(·) represents a two-dimensional mask, which is a two-dimensional matrix of the same size as U(x,y); ρ0 is the detection threshold; and I′(x,y) is the two-dimensional raster image after masking.

[0073] In other words, when mask(x,y) = 1, it means there is no interference, and I′(x,y) outputs according to the original two-dimensional raster image I(x,y). When mask(x,y) = 0, it means there is interference, and I′(x,y) sets the pixel at this location to zero, in order to filter out the points in that location.

[0074] Therefore, interference points are filtered based on the masked two-dimensional raster image I′(x,y), and points in pixels with a pixel value of 0 are removed. New point images are generated using the retained points.

[0075] Through the above embodiments, this invention first obtains a multi-period distribution map of the surrounding environment based on a large amount of collected point data. Then, according to the distribution characteristics of the points, the point distribution map is rasterized in polar coordinates, and the raster is divided according to a certain sampling interval to establish a corresponding two-dimensional raster map. Utilizing the characteristic that the points of interfering ground features in the polar coordinate system exhibit a linear distribution on the point map after multi-period superposition, a sliding window detection method along the azimuth direction is used to determine the distribution location of interfering points, forming a specific two-dimensional mask. Finally, the raster map processed by the mask is used to filter points in the area to be detected. Therefore, this invention can accurately and effectively mask the area where interfering points are located without interfering with the effective points of the target, thereby significantly reducing the generation of interfering flight paths.

[0076] Based on the methods disclosed above, the present invention also provides an exemplary embodiment for illustrative purposes.

[0077] In an exemplary embodiment of the present invention, real point data recorded by a ground-based surveillance radar is provided. The main radar operating parameters of this data are: band X, pulse accumulation of 256, and number of superposition periods of 1024. Some point data are shown below for illustration.

[0078] (1) Multiple periodic points are superimposed, and a point distribution map is drawn based on the point coordinates. The point distribution map is divided into grids according to the sampling interval of 0.01 degrees in the azimuth direction and 5 meters in the distance direction to generate a two-dimensional grid map.

[0079] Figure 4 The illustration shows a dot distribution map drawn according to an exemplary embodiment of the present invention. Figure 5 The illustration schematically shows a two-dimensional grid diagram corresponding to an exemplary embodiment of the present invention.

[0080] A local area of ​​the dot plot drawn based on coordinates, as shown below. Figure 4 As shown, the corresponding two-dimensional raster image is as follows: Figure 5 As shown. From Figure 4 It can be seen that a large number of linearly extending dots are mixed in with the target track, affecting the detection of moving targets. The same characteristic is present in... Figure 5 This can also be reflected in the text. Figure 5 There are also a lot of white lines in it.

[0081] (2) Based on experience, design a 50-meter long azimuth sliding window to act on the entire two-dimensional grid map. If the number of white pixels in the area covered by the sliding window exceeds 15, the pixels in the sliding window are judged as interfering pixels, that is, unintentional interference from the ground environment.

[0082] (3) The mask value is set to 0 at the location of the interference pixel and 1 at other locations, and finally a matrix of two-dimensional masks of the same size as the raster is generated.

[0083] Figure 6 The illustration schematically shows a two-dimensional mask generated according to an exemplary embodiment of the present invention. The grayscale display of the two-dimensional mask is as follows. Figure 6 As shown.

[0084] Figure 7 The diagram schematically illustrates a two-dimensional raster image after masking according to an exemplary embodiment of the present invention.

[0085] (4) Apply the above two-dimensional mask to the original two-dimensional raster image. The resulting two-dimensional raster image after masking is as follows: Figure 7 As shown, the white lines have been filtered out.

[0086] (5) Based on the new two-dimensional raster image (i.e., the two-dimensional raster image after masking), discard the interference points contained in the pixel with a pixel value of 0, and the remaining points are the target points.

[0087] Figure 8 The illustration schematically shows a new dot pattern after filtering out interfering dots according to an exemplary embodiment of the present invention.

[0088] To make the results more intuitive, a new dot pattern is drawn using the preserved dots, as shown below. Figure 8 As shown, comparison Figure 4 It can be seen that the linearly arranged dots are eliminated, while the target dots remain intact, indicating that this method is effective in eliminating interfering dots.

[0089] In summary, this invention discloses a method for removing unintentional interference points based on prior point information. It involves rasterizing the point distribution map obtained by superimposing multiple radar scan cycles to form a two-dimensional raster map. Then, by counting the number of pixels containing point traces within a sliding window, the locations of interference points are identified. Finally, the interference points contained in the pixels at these locations are filtered out, resulting in a radar point map with interference points removed. (Comparison) Figure 4 and Figure 8 It can be seen that the method of the present invention can effectively remove a large number of linear dots caused by unintentional interference, and can preserve the target dots relatively completely.

[0090] This concludes the detailed description of this embodiment with reference to the accompanying drawings. Based on the above description, those skilled in the art should have a clear understanding of the interference dot removal method provided by this invention.

[0091] Based on the same inventive concept, this invention also provides a device for removing unintentional interference dots based on prior dot information, which will be described below in conjunction with... Figure 9 The device is described in detail.

[0092] Figure 9A block diagram of an unintentional interference mark removal device based on prior mark information according to an embodiment of the present invention is shown schematically.

[0093] like Figure 9 As shown, the unintentional interference mark removal device 900 based on prior mark information according to this embodiment includes a mark acquisition module 910, a rasterization module 920, a mask generation module 930, and an interference filtering module 940.

[0094] The dot acquisition module 910 is used to acquire dot data from multiple periods in the same scene and generate a dot distribution map.

[0095] The rasterization module 920 is used to rasterize the point distribution map to generate a two-dimensional raster map.

[0096] The mask generation module 930 is used to determine the distribution location of interference points along the orientation of the two-dimensional grid image using a sliding window detection method, and generate a two-dimensional mask.

[0097] The interference filtering module 940 is used to perform masking processing on a two-dimensional raster image using a two-dimensional mask, and to filter out interference points from the masked two-dimensional raster image to generate a new point image.

[0098] It should be noted that the embodiments of the device section are similar to those of the method section, and the technical effects achieved are also similar. For specific details, please refer to the above-mentioned method embodiment section, which will not be repeated here.

[0099] According to embodiments of the present invention, any plurality of the point acquisition module 910, the rasterization module 920, the mask generation module 930, and the interference filtering module 940 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of the present invention, at least one of the point acquisition module 910, the rasterization module 920, the mask generation module 930, and the interference filtering module 940 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in hardware or firmware, or in any one of software, hardware, and firmware implementations, or in a suitable combination of any of these. Alternatively, at least one of the dot acquisition module 910, rasterization module 920, mask generation module 930, and interference filtering module 940 may be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0100] It should be noted that implementations not illustrated or described in the accompanying drawings or the main text of the specification are all forms known to those skilled in the art and are not described in detail. Furthermore, the definitions of the various elements and methods described above are not limited to the specific structures, shapes, or methods mentioned in the embodiments, and those skilled in the art can easily modify or substitute them.

[0101] The accompanying drawings show some block diagrams and / or flowcharts. It should be understood that some blocks or combinations thereof in the block diagrams and / or flowcharts can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when executed by the processor, these instructions can create means for implementing the functions / operations described in these block diagrams and / or flowcharts.

[0102] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified. Furthermore, the word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements.

[0103] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for eliminating unintentional track based on prior track information, characterized in that, The method comprises the following steps: S1, acquiring multi-period point trail data under the same scene to generate a point trail distribution map; S2, performing rasterization processing on the point trail distribution map to generate a two-dimensional raster map; S3, using a sliding window detection method to determine the distribution position of the interference point trail along the azimuth direction of the two-dimensional raster map to generate a two-dimensional mask; S4, performing mask processing on the two-dimensional raster map using the two-dimensional mask, and filtering out the interference point trail using the two-dimensional raster map after the mask processing to generate a new point trail map; The step S3 specifically comprises: S31, calculating the pixel density of the interference point trail in each sliding window along the azimuth direction of the two-dimensional raster map by using the sliding window detection method; S32, setting a detection threshold to determine whether the pixel density in each sliding window is greater than the detection threshold, if yes, the pixel in the sliding window is determined as ground environment unintentional interference, and the mask value at the corresponding position is set to 0; otherwise, the mask value at the corresponding position is set to 1; S33, repeating the steps S31-S32 to generate the two-dimensional mask through the distance gate sliding window detection one by one; In the step S31, the pixel density of the interference point trail in each sliding window is calculated according to the following formula: where N is a preset azimuth sliding window length; p x,y is the pixel density of the existing interference point traces in the sliding window of size N; I(x, y) is a two-dimensional matrix of a two-dimensional grid map, including azimuth angle coordinate x and distance coordinate y; The two-dimensional mask and the two-dimensional raster map after the mask processing are calculated according to the following formula: In the formula, mask(·) represents a two-dimensional mask, which is a two-dimensional matrix of the same size as I(x, y); For a detection threshold; For the two-dimensional grid map after mask processing.

2. The method of claim 1, wherein, The step S1 specifically comprises: S11, acquiring multi-period point trail data under the same scene by a ground-based radar, wherein the point trail data comprises azimuth angle and distance information; S12, superimposing and displaying the multi-period point trail data to draw the point trail distribution map in a polar coordinate system of distance-azimuth angle.

3. The method of claim 2, wherein, The step S2 specifically comprises: According to a preset azimuth sampling interval and a distance sampling interval, the point trail distribution map is divided into grids to generate the two-dimensional raster map.

4. The method of claim 3, wherein the method further comprises: The azimuth sampling interval and the distance sampling interval are selected according to the angle measurement accuracy and the distance measurement resolution of the ground-based radar.

5. The method of claim 3, wherein the step of determining the probability of the false track is performed by using a Bayesian network. The point trail distribution map is divided into grids, which comprises projecting the point trail data onto the two-dimensional raster map according to the following formula: In the formula, I(x, y) is a two-dimensional matrix of the two-dimensional raster map; tar_point is a coordinate set of the point trail after quantization according to the sampling interval, which comprises an azimuth angle coordinate x and a distance coordinate y.

6. An unintentional clutter plot elimination device based on prior plot information, characterized by The device is used for executing the unintentional interference point trail elimination method based on prior point trail information in any one of claims 1-5, and the device comprises: A point trail acquisition module is configured to acquire multi-period point trail data under the same scene to generate a point trail distribution map; A rasterization module is configured to perform rasterization processing on the point trail distribution map to generate a two-dimensional raster map; A mask generation module is configured to use a sliding window detection method to determine the distribution position of the interference point trail along the azimuth direction of the two-dimensional raster map to generate a two-dimensional mask; An interference filtering module is configured to perform mask processing on the two-dimensional raster map using the two-dimensional mask, and filter out the interference point trail using the two-dimensional raster map after the mask processing to generate a new point trail map.

Images