A radar monitoring target point selection method

Abstract

The application provides a radar monitoring target point selection method, comprising the following steps: coarsely selecting a range where a target point is located in a radar monitoring range, constructing a set W by using cell numbers in the range where the coarsely selected target point is located; sorting corresponding cells in the set W according to signal strength from strong to weak, constructing a set U by using cell numbers corresponding to the first k cells, and calculating a deformation value mean; for each frame of radar deformation monitoring data, performing cosine similarity calculation on deformation values corresponding to single cell numbers in the set W and the deformation value mean, and realizing target point selection. The application selects cell numbers on the corner reflector by signal strength sorting first, then calculates the deformation value mean of the selected k cells, obtains the deformation trend of the monitoring point on the corner reflector, and finally screens the points in the set W which have the same deformation trend as the deformation value mean through cosine similarity, so as to reduce the possibility of misselection when selecting the target point.

Description

Technical Field

[0001] The present invention relates to the field of radar monitoring technology, and in particular to a method for selecting target points for radar monitoring. Background Art

[0002] Arc-shaped synthetic aperture deformation monitoring radars can monitor deformation over a wide area. Their monitoring range is a sector, divided into several smaller sector cells based on range and angular resolution. The monitoring result is the cumulative deformation within each sector cell relative to the initial monitoring time. The monitored target is often represented by multiple cells in the radar results. To monitor and analyze the target, it is necessary to select an appropriate number of target point cells, but a unified method for selecting these cells is currently lacking.

[0003] In the process of selecting the target point cell, if a point on the ground is selected by mistake, the actual deformation of the corner reflector setting area cannot be accurately reflected, which will have an adverse impact on the surface deformation monitoring.

[0004] In summary, there is an urgent need for a radar monitoring target point selection method to solve the problems existing in the existing technology. Summary of the Invention

[0005] The present invention aims to provide a method for selecting target points for radar monitoring, so as to solve the problem of target point selection during radar monitoring.

[0006] To achieve the above object, the present invention provides a method for selecting a radar monitoring target point, comprising the following steps:

[0007] Step 1: Divide the radar monitoring range into cells and number each cell. Roughly select the target point range within the radar monitoring range, and construct a set W based on the cell numbers within the roughly selected target point range.

[0008] Step 2: Sort the corresponding cells in the set W by signal strength from strong to weak, and select the cell numbers corresponding to the first k cells to construct the set U, where k ≥ 2;

[0009] Step 3: Select n consecutive frames of radar deformation monitoring data and calculate the mean deformation value corresponding to the k cell numbers in the set U in each frame of radar deformation monitoring data;

[0010] Step 4: For each frame of radar deformation monitoring data, the cosine similarity between the deformation value corresponding to a single cell number in the set W and the mean of the deformation values ​​is calculated. When the cosine similarity is above the set threshold, the cell number is stored in the target point set T.

[0011] Preferably, in the step 1, the radar monitoring range is divided into cells to form a fan-shaped grid, and the entire radar monitoring range has M rows×N columns of cells, and the cell in the i-th row and j-th column is numbered (i, j);

[0012] Taking the cell with the strongest signal strength in the area where the target point of the corner reflector to be selected is located as the center point, use a polygon, rectangle or circle to circle the range where the target point is located. The range where the roughly selected target point is located should only include cells covered by one corner reflector and its surrounding area. The number of cell numbers in the set W is more than 200.

[0013] Preferably, in step 2, the signal strength ranges from -50.0 to 0.0 db.

[0014] Preferably, in step 3, n is greater than or equal to the number of radar scans within 24 hours, and in the t-th frame radar deformation monitoring data, the mean deformation value Z of the cells corresponding to the k cell numbers in the set U is U (t) is determined by expression 1):

[0015]

[0016] Among them, Z p (t) is the deformation value corresponding to the p-th cell number in the set U in the t-th frame of radar deformation monitoring data.

[0017] Preferably, in the step 4, in the t-th frame radar deformation monitoring data, the cosine similarity cos of the cell corresponding to the q-th cell number in the set W is q (t) is determined by expression 2):

[0018]

[0019] Among them, Z q (t) is the deformation value corresponding to the qth cell number in the set W in the tth frame of radar deformation monitoring data.

[0020] Preferably, in step 4, when cos q When (t)≥val, the qth cell number is stored in the target point set T, where val is the set threshold and val≥0.98.

[0021] Preferably, a radar monitoring target point selection method also includes step five: constructing the deformation value corresponding to the x-th cell number in the target point set T in n frames of radar deformation monitoring data into an array Bx in chronological order, and analyzing the deformation trend of the target point through Bx.

[0022] The application of the technical solution of the present invention has the following beneficial effects:

[0023] (1) In the present invention, since the points with the strongest signal strength in the rough selection range are basically the monitoring points on the corner reflector, the cell numbers with high probability on the corner reflector are first selected by signal strength sorting, and then the deformation trend of the monitoring points on the corner reflector is obtained by calculating the mean deformation value of the selected k cells. Finally, the points in the set W with the same deformation trend as the mean deformation value are filtered by cosine similarity. Since the deformation trends of the surface interference points and the points on the corner reflector are different, the cells with the same deformation trends are filtered by cosine similarity to obtain the cells corresponding to the target points on the corner reflector, thereby reducing the possibility of misselecting surface points when selecting target points only by signal strength.

[0024] (2) In the present invention, when roughly selecting the target point range, the cell with the strongest signal strength in the area where the target point of the corner reflector to be selected is located is used as the center point, and a polygon, rectangle or circle is used to circle the target point range. The roughly selected target point range should only include cells covered by one corner reflector and its surrounding area to avoid other corner reflectors from affecting the selection result of the corner reflector of the target point to be selected.

[0025] (3) In the present invention, the mean deformation value is calculated by selecting k points with the strongest signal strength, and the points with strong signal strength within the rough selection range are basically concentrated on the corner reflector, which can minimize the error caused by surface interference points in calculating the mean deformation value.

[0026] (4) In the present invention, the mean deformation value corresponding to the cell number in the set U in n frames of radar deformation monitoring data is obtained, where n is greater than or equal to the number of radar scans within 24 hours. All radar monitoring results within one day can be obtained, thereby reducing the errors caused by changes in atmospheric factors within one day.

[0027] (5) In the present invention, the cell numbers of several target points are stored in the target point set T, and the deformation values ​​of these target points are used to analyze the deformation and deformation trend of the area to determine the deformation speed and whether an early warning is needed, thereby providing target point data for subsequent surface deformation monitoring.

[0028] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0030] Figure 1This is a schematic diagram of the cell division of the radar monitoring range in step 1 of the embodiment of the present application;

[0031] Figure 2 This is a schematic diagram of the range of the roughly selected target point in step 1 of the embodiment of the present application;

[0032] Figure 3 is a schematic diagram of the target point set selected in step 4 of the embodiment of the present application;

[0033] Among them, 1. Radar monitoring range, 2. Cell. DETAILED DESCRIPTION

[0034] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. However, the present invention can be implemented in many different ways as defined and covered by the claims.

[0035] Example:

[0036] See also Figures 1 to 3 , a radar monitoring target point selection method, this embodiment is applied to the selection of GBSAR target points.

[0037] A method for selecting a target point for radar monitoring comprises the following steps:

[0038] Step 1: See Figure 1 , divide the radar monitoring range 1 into cells, and number each cell 2, roughly select the range where the target point is located within the radar monitoring range, and construct a set W based on the cell numbers within the range where the roughly selected target point is located;

[0039] See also Figure 1 The radar monitoring range obtained by ground-based synthetic aperture radar (GBSAR) is a sector-shaped structure. After cell division, it forms a sector-shaped grid. Each cell is a sector unit. There are M rows × N columns of cells in the entire radar monitoring range. M is the number of cells in the range direction, and N is the number of cells in the angle direction. The values ​​of M and N are determined by the angular resolution △θ, the range resolution △r, and the radar monitoring range. The cell number of the i-th row and j-th column is (i, j), 1≤i≤M, 1≤j≤N; the radar monitoring results are divided into deformation data and signal strength data, among which the deformation data is the cumulative deformation value relative to the initial monitoring time. Each frame of radar monitoring data has M×N cumulative deformation monitoring values; the signal strength data is the signal strength reflected by the radar, with a value range of -50.0~0.0db. Each frame of radar monitoring data has M×N signal strength values.

[0040] Taking the cell with the strongest signal strength in the area where the target point of the corner reflector to be selected is located as the center point, use a polygon, rectangle or circle to circle the range where the target point is located. The range where the target point is roughly selected should only include cells covered by one corner reflector and its surrounding area. The number of cell numbers in the set W should be more than 200 to avoid other corner reflectors affecting the selection result of the corner reflector to be selected.

[0041] The target points on the corner reflector are composed of multiple cells. Due to the structural characteristics of the corner reflector, the signal intensity reflected by the center of the corner reflector facing the radar is the strongest compared to the signal intensity of other surrounding points. Therefore, the coarse selection range is defined with the point with the strongest signal intensity as the center. This ensures that all target points on the corner reflector are within the coarse selection range. That is, the cell numbers corresponding to all target points on the corner reflector are in the set W, avoiding the situation where target points are missed.

[0042] In this embodiment, see Figure 2 Using a rectangle as the selection range, roughly select the cell range of the corner reflector containing the target point to be selected within the radar monitoring range. The row numbers in the set W range from 1200 to 1294, and the column numbers range from 658 to 709.

[0043] Step 2: Sort the corresponding cells in set W by signal strength from strong to weak, and select the cell numbers corresponding to the first k cells to construct set U, where k ≥ 2. This is because when the corner reflector is set on the ground, if the distance from point A on the corner reflector to the radar is similar to the distance from point B on the ground to the radar, the two points will be relatively close in the radar image. In this case, the image of point B on the ground is in set W, but the signal strength of point B is definitely weaker than that of point A. Therefore, the interference point B can be excluded by signal strength sorting. This facilitates the subsequent steps to obtain the deformation trend of the corner reflector as the ground deforms through the cells corresponding to the cell numbers in set U.

[0044] In this embodiment, the signal strength range of the cells corresponding to the cell numbers in set W is -50.0 to 0.0 dB, k=4, and in set W, the four cells with the strongest signal strength are numbered (1248, 679), (1249, 679), (1250, 679) and (1250, 678).

[0045] Step 3: Select n consecutive frames of radar deformation monitoring data and calculate the mean deformation value corresponding to the k cell numbers in the set U in each frame of radar deformation monitoring data;

[0046] n is greater than or equal to the number of radar scans within 24 hours, and all radar monitoring results within a day can be obtained. In this embodiment, the radar monitoring interval is 45 minutes, and a total of 32 scans are performed within 24 hours, obtaining 32 frames of radar deformation monitoring data. In this embodiment, n=32 to reduce errors caused by changes in atmospheric factors within a day.

[0047] In n frames of radar deformation monitoring data, for each cell number in the set U, the deformation value corresponding to the cell number is extracted in each frame of radar deformation monitoring data according to its row and column numbers, and arranged into an array Zp in increasing order of time, 1≤p≤k, p is a positive integer. There are n deformation values ​​in the array Zp, that is, Z p (1) Z p (2)……Z p (n-1), Z p (n), in this embodiment, there are 32 deformation values ​​in the array Zp.

[0048] In the t-th frame radar deformation monitoring data, the mean deformation value Z of the cells corresponding to the k cell numbers in the set U is U (t) is determined by expression 1):

[0049]

[0050] Among them, Z p (t) is the deformation value corresponding to the p-th cell number in the t-th frame radar deformation monitoring data in the set U. The mean value Z of the n deformation values ​​obtained in the n-frame radar deformation monitoring data is U (t) forms an array Z U , including Z U (1) Z U (2)……Z U (n-1), Z U (n).

[0051] In this embodiment, Z U =[-0.0341 -0.0965 -0.1534 -0.2229 -0.3043 -0.2747 -0.4040 -0.4597 -0.5325 -0.7098 -0.8110 -0.9292 -1.0376 -1.1017 -1.3301 -1.4702 -1.5542 -1.8733 -1.9592 -1.7415 -1.5151 -1.6902 -1.7712 -1.7205 -1.8550 -1.4492 -1.1733 -1.2854 -1.2947 -1.5361 -1.7146 -1.9438].

[0052] Step 4: For each frame of radar deformation monitoring data, the cosine similarity between the deformation value corresponding to a single cell number in the set W and the mean of the deformation values ​​is calculated. When the cosine similarity is above the set threshold, the cell number is stored in the target point set T.

[0053] For each cell number in the set W, its deformation value is extracted from each frame of radar deformation monitoring data according to its row and column numbers, and arranged into an array Zq in increasing order of time, where q is a positive integer and 1≤q≤COUNT(W), COUNT(W) is the total number of cell numbers in the set W. In this embodiment, COUNT(W)=4940, and each array Zq contains n deformation values, that is, Z q (1) Z q (2)……Z q (n-1), Z q (n).

[0054] In the t-th frame of radar deformation monitoring data, the cosine similarity of the cell corresponding to the q-th cell number in the set W is cosine q (t) is determined by expression 2):

[0055]

[0056] Among them, Z q (t) is the deformation value corresponding to the qth cell number in the set W in the tth frame of radar deformation monitoring data.

[0057] When cos q When (t)≥val, the qth cell number is stored in the target point set T, where val is the set threshold and val≥0.98.

[0058] In this application, since the points with the strongest signal strength in the rough selection range are basically the monitoring points on the corner reflector, the cell numbers with high probability on the corner reflector are first selected by signal strength sorting, and then the deformation trend of the monitoring points on the corner reflector is obtained by taking the mean deformation value of the selected k cells, and finally the points in the set W with the same deformation trend as the mean deformation value are filtered by cosine similarity. This is because when the ground is deformed, the position of the corner reflector moves, which is reflected in the radar monitoring results as deformation. However, in the process of the corner reflector moving, the different positions of the corner reflector are affected by the surface deformation. For different radar directions, their deformation values ​​are slightly different, but the deformation trends of all target points on the corner reflector are consistent. Although the points on the ground have higher signal strength, their deformation trends are quite different from those of the target points on the corner reflector because the ground and the corner reflector belong to different areas. If only the signal strength is used to judge the target point, the point on the ground may be mistakenly selected as the target point on the corner reflector. Therefore, by using cosine similarity to filter cells with the same deformation trend, the cells corresponding to the target points on the corner reflector can be obtained, reducing the possibility of misselection.

[0059] The target point corresponding area extracted in this application is as follows Figure 3 As shown in the white area.

[0060] Step 5: Construct the deformation values ​​corresponding to the x-th cell number in the target point set T in n frames of radar deformation monitoring data into an array Bx in chronological order, and analyze the deformation trend of the target point through the array Bx.

[0061] When the corner reflector is displaced due to surface deformation, its direction facing the radar will change, causing the point on the corner reflector facing the radar center to change. Therefore, selecting a single point as the target point for surface deformation will result in errors and cannot fully reflect the deformation trend of this area. Therefore, the cell numbers of several target points are stored in the target point set T. The deformation values ​​of these target points are used to analyze the deformation and deformation trend of the area to determine the deformation speed and whether an early warning is needed, thereby providing target point data for subsequent surface deformation monitoring.

[0062] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A radar monitoring target point selection method, characterized in that: The following steps are involved: Step 1: Divide the radar monitoring range into cells and number each cell. Roughly select the target point range within the radar monitoring range, and construct a set W based on the cell numbers within the roughly selected target point range. Step 2: Sort the corresponding cells in the set W by signal strength from strong to weak, and select the cell numbers corresponding to the first k cells to construct the set U, where k ≥ 2; Step 3: Select n consecutive frames of radar deformation monitoring data and calculate the mean deformation value corresponding to the k cell numbers in the set U in each frame of radar deformation monitoring data; Step 4: For each frame of radar deformation monitoring data, the cosine similarity between the deformation value corresponding to a single cell number in the set W and the mean of the deformation values ​​is calculated. When the cosine similarity is above the set threshold, the cell number is stored in the target point set T.

2. A radar monitoring target point selection method according to claim 1, characterized in that: In the step 1, the radar monitoring range is divided into cells to form a fan-shaped grid, and the entire radar monitoring range has M rows×N columns of cells, and the cell in the i-th row and j-th column is numbered (i, j); Taking the cell with the strongest signal strength in the area where the target point of the corner reflector to be selected is located as the center point, use a polygon, rectangle or circle to circle the range where the target point is located. The range where the roughly selected target point is located should only include cells covered by one corner reflector and its surrounding area. The number of cell numbers in the set W is more than 200.

3. The radar monitoring target point selection method according to claim 1, characterized in that: In the step 2, the signal strength ranges from -50.0 to 0.0 db.

4. The radar monitoring target point selection method according to claim 2, characterized in that: In step 3, n is greater than or equal to the number of radar scans within 24 hours, and in the t-th frame radar deformation monitoring data, the mean deformation value Z of the cells corresponding to the k cell numbers in the set U is U (t) is determined by expression 1): Among them, Z p (t) is the deformation value corresponding to the p-th cell number in the set U in the t-th frame of radar deformation monitoring data.

5. A radar monitoring target point selection method according to claim 4, characterized in that: In the step 4, in the t-th frame of radar deformation monitoring data, the cosine similarity cos of the cell corresponding to the q-th cell number in the set W is q (t) is determined by expression 2): Among them, Z q (t) is the deformation value corresponding to the qth cell number in the set W in the tth frame of radar deformation monitoring data.

6. A radar monitoring target point selection method according to claim 5, characterized in that: In the step 4, when cos q When (t)≥val, the qth cell number is stored in the target point set T, where val is the set threshold and val≥0.

98.

7. A radar monitoring target point selection method according to claim 6, characterized in that: The method further includes step five: constructing an array Bx according to the time sequence of the deformation values ​​corresponding to the x-th cell number in the target point set T in the n-frame radar deformation monitoring data, and analyzing the deformation trend of the target point through the array Bx.

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