Slope radar monitoring data and video image fitting display method

Abstract

The invention discloses a slope radar monitoring data and video image fitting display method. The method comprises the steps that a plurality of corner reflectors are arranged on the surface of a slope of a monitoring area; constructing a radar image coordinate system of the side slope radar imaging picture, determining the position of the corner reflector in the side slope radar imaging picture, and determining the image coordinate value of the corner reflector through the image coordinate system; constructing a video image coordinate system, and manually marking the image coordinate value of the corner reflector in the frame of slope video monitoring image; establishing an affine transformation matrix between the side slope radar imaging picture and the side slope video monitoring image, and synchronously fitting the side slope radar imaging picture and the one-magnification side slope video stream based on the affine transformation matrix, determining the position of a target query point in the slope video monitoring image with different magnifications in the slope video monitoring image with one magnification; according to the invention, the visualization effect of slope radar monitoring data is improved, and the real-time performance and accuracy of monitoring are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of slope monitoring, and in particular to a method for displaying slope radar monitoring data and video images in conjunction with each other. Background Art

[0002] Slope radar realizes real-time imaging of the slopes in the monitoring area by emitting microwaves. In order to more intuitively view and display the slope displacement monitoring data in the imaging map, it is usually necessary to perform three-dimensional spatial registration between the slope radar imaging map and the UAV three-dimensional aerial survey map.

[0003] UAV aerial survey, massive data processing and modeling, aerial survey base map and elevation processing, and the development of registration software are the basic work to complete the registration. The entire registration process not only requires high computer computing power, but is also very cumbersome.

[0004] The traditional way of fitting radar data to video surveillance images is to take an overall image of the entire open-pit mine, use 3D modeling software to build a 3D real-life model of the open-pit mine, and use the video surveillance image as a base map. The computing power of different computers varies, and it usually takes more than 4 hours to model 100 photos.

[0005] When the radar monitoring image is fitted with the video monitoring image, it is also necessary to construct a radar stereo image based on the radar coordinates (which need to be measured in advance with RTK or total station), 84 coordinate point cloud, and UTM coordinate point cloud, and then fit the radar stereo image with the video monitoring base map. The entire fitting operation takes at least 30 minutes. Therefore, the traditional fitting display of video monitoring images and radar monitoring images takes a long time, and real-time updating of video monitoring data and radar monitoring data cannot be achieved. Especially for open-pit mine slopes, the slope surface scene continues to change with the progress of mining activities, resulting in a mismatch in the timing between the radar monitoring image and the aerial survey base map, which seriously affects the slope radar monitoring effect. Summary of the invention

[0006] The purpose of the present invention is to provide a method for displaying slope radar monitoring data and video images in combination, so as to solve the technical problem that there is a mismatch between the timing of radar monitoring images and aerial survey base maps in the prior art, which seriously affects the slope radar monitoring effect.

[0007] In order to solve the above technical problems, the present invention specifically provides the following technical solutions: A method for displaying slope radar monitoring data and video images in combination, comprising the following steps: Step 100: Divide the open-pit mine into different monitoring areas, arrange multiple corner reflectors on the slope surface of each monitoring area, and install corresponding slope radar and video monitoring equipment opposite to each monitoring area; Step 200: construct a radar image coordinate system of the slope radar image, determine the position of the corner reflector in the slope radar image based on the strength of the echo signal in the slope radar image, and determine the image coordinate value of the corner reflector through the image coordinate system. ; Step 300: intercept the slope video monitoring image from the slope video stream in the monitoring area, construct the video image coordinate system, and manually mark the image coordinate value of the corner reflector in the slope video monitoring image frame. ; Step 400: Establish an affine transformation matrix between the slope radar imaging image and the slope video monitoring image so that the image coordinate value of the corner reflector in the image coordinate system is The image coordinate value of the corner reflector in the video image coordinate system There is a one-to-one correspondence between them; Step 500: Synchronize and fit the slope radar imaging image with the 1-magnification slope video stream based on the affine transformation matrix, determine the position of the target query point in the slope video surveillance image at different magnifications in the 1-magnification slope video surveillance image, and obtain the radar monitoring data corresponding to the target query point in the slope video surveillance image at different magnifications in the slope radar imaging image.

[0008] As a preferred solution of the present invention, in step 100, all corner reflectors are evenly dispersed on the slope surface, the number of corner reflectors arranged on the slope surface is at least 3, and each reflecting surface of each corner reflector is unobstructed.

[0009] As a preferred solution of the present invention, in step 200, the radar image coordinate system is used to express the coordinate system of each pixel position in the slope radar imaging image, and the origin of the radar image coordinate system is set at the upper left corner of the slope radar imaging image; The echo signal of the corner reflector in the slope radar imaging image is stronger than the echo signal of the slope surface in the slope radar imaging image, so that the pixel value of the corner reflector in the slope radar imaging image is greater than the pixel value corresponding to the slope rock surface in the slope radar imaging image.

[0010] As a preferred solution of the present invention, the image resolution of the slope radar imaging image is m×n pixels, the slope radar imaging image is subjected to wave intensity filtering, the pixel value corresponding to each pixel point in the slope radar imaging image after wave intensity filtering is collected, the pixel points are screened out based on the pixel values, and the image coordinates of the screened pixel points in the radar image coordinate system of the slope radar imaging image are determined. .

[0011] As a preferred solution of the present invention, in step 300, the image resolution of the slope video monitoring image is o×p pixels.

[0012] As a preferred solution of the present invention, in step 400, the implementation method of establishing the affine transformation matrix between the slope radar imaging image and the slope video monitoring image is: Using the slope video surveillance image as a base map, the slope radar imaging image is mapped to the slope video surveillance image through an affine transformation matrix, and the pixel coordinates of the slope radar imaging image after affine transformation by the affine transformation matrix are matched one by one with the pixel coordinates on the slope video surveillance image; Among them, the expression of the affine transformation matrix is: ; The coordinates of the slope radar image after affine transformation by the affine transformation matrix; are the coordinates of the slope radar image before affine transformation; is the affine transformation matrix, where , , , , and are the affine transformation parameters.

[0013] As a preferred solution of the present invention, the implementation method of mapping the slope radar imaging image to the slope video monitoring image through an affine transformation matrix is: Input the coordinate values ​​of each corner reflector in the slope radar imaging image and the slope video monitoring image to obtain the affine transformation matrix , , , , and ; The slope radar imaging image, affine transformation matrix and the size of the output image are input into the Python software. The pixel coordinates of the slope radar imaging image after the affine transformation matrix are identical to the coordinates of the same pixel points on the slope video surveillance image.

[0014] As a preferred solution of the present invention, all pixel points on the slope radar imaging image are traversed one by one, and the coordinate value corresponding to each pixel point is obtained based on the image coordinate system; After the coordinate value of each pixel point on the slope radar imaging image is converted through the affine transformation matrix, it is the same as the coordinate value of the same pixel point on the slope video surveillance image, so that the slope radar imaging image is transformed into a slope radar monitoring cloud map that matches the pixel points of the slope video surveillance image one by one.

[0015] As a preferred solution of the present invention, the implementation method of obtaining the radar monitoring data corresponding to the radar imaging image of the slope by the target query point of the slope video monitoring image at different magnifications is as follows: First, determine the position of the target query point in the slope video monitoring image with different magnifications in the slope video monitoring image with 1 magnification; Based on the position of the target query point in the 1-magnification slope video monitoring image, the position of the target query point corresponding to the slope radar imaging image after affine transformation is determined, thereby obtaining the radar monitoring data corresponding to the target query point in the slope radar imaging image.

[0016] As a preferred solution of the present invention, the method for determining the position of the target query point in the slope video monitoring image with different magnifications in the slope video monitoring image with 1 magnification is as follows: ; in, is the image plane coordinates of the target query point in the slope video monitoring image with different magnifications in the 1-magnification image; are the image plane coordinates of the optical axis center of the slope video monitoring image with different magnifications in the 1-magnification image; are respectively the image plane coordinates of the target query point in the slope video monitoring image at different magnifications; M is the video image magnification.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The present invention performs radar monitoring and video monitoring on the slope, and displays the slope displacement monitoring data contained in the slope radar imaging image in the slope video monitoring image, thereby realizing real-time updating of the slope video monitoring base map, significantly improving the visualization effect of the slope radar monitoring data, improving the real-time and accuracy of monitoring, and providing more intuitive and effective technical support for slope monitoring and early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0019] Figure 1 A flow chart of a method for displaying monitoring data and video images in conjunction with each other according to an embodiment of the present invention; Figure 2 A schematic diagram of the coordinate position of a corner reflector in a radar image coordinate system according to an embodiment of the present invention; Figure 3 A schematic diagram of the coordinate position of a corner reflector in a video image coordinate system according to an embodiment of the present invention; Figure 4 The radar imaging image of the slope before affine transformation according to the embodiment of the present invention; Figure 5 The slope radar imaging image after affine transformation according to an embodiment of the present invention; Figure 6 It is a fitting diagram of the slope radar imaging image and the slope video monitoring image after affine transformation according to an embodiment of the present invention; Figure 7 This is a diagram showing the fitting display effect of the slope video monitoring base map and the radar monitoring cloud map according to an embodiment of the present invention; Figure 8 Schematic diagram of the pixel positioning principle of images with different magnifications according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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.

[0021] like Figure 1 As shown, the present invention provides a method for displaying slope radar monitoring data and video images in combination, comprising the following steps: Step 100: Divide the open-pit mine into different monitoring areas, arrange multiple corner reflectors on the slope surface of each monitoring area, and install corresponding slope radar and video monitoring equipment opposite to each monitoring area.

[0022] All corner reflectors are evenly dispersed on the slope surface, the number of corner reflectors arranged on the slope surface is at least 3, and each reflecting surface of each corner reflector is unobstructed.

[0023] The video and radar monitoring operations of the open-pit mine are monitored in a zoned manner. The open-pit mine is divided into multiple plane blocks, and slope radars and video monitoring equipment are installed in opposite directions of each plane block, so as to realize radar monitoring and video monitoring of each plane block. Since the video stream is transmitted and updated in real time, there is no time consumption, and the radar monitoring data and video monitoring data are two-dimensionally fitted, there is no three-dimensional modeling problem, there is no requirement for computer performance, and time consumption is not considered.

[0024] Step 200: construct a radar image coordinate system of the slope radar image of the monitoring area, determine the position of the corner reflector in the slope radar image based on the strength of the echo signal in the slope radar image, and determine the image coordinate value of the corner reflector through the image coordinate system ,like Figure 2 shown.

[0025] Step 300: intercept the slope video monitoring image from the slope video stream in the monitoring area, construct the video image coordinate system, and manually mark the image coordinate value of the corner reflector in the slope video monitoring image frame. ,like Figure 3 shown.

[0026] It should be noted that, in the present embodiment, a slope radar and a video surveillance device are arranged opposite to the monitoring area. The slope radar and the video surveillance device can respectively collect radar data and video data of the same monitoring area. Both the radar data and the video data are two-dimensional data. When the radar data and the video data are fitted, a frame of image is captured from the video stream, and the monitoring time of the image is determined. Then, the radar imaging image of the same monitoring time is obtained, and the affine transformation matrix of the video surveillance image and the radar imaging image is solved using the opencv software library of python. The imaging images generated by the subsequent radar (the imaging image here is another format of the radar monitoring data) can be transformed by this affine transformation matrix.

[0027] In step 200, the radar image coordinate system is used to express the coordinate system of each pixel position in the slope radar imaging image, and the origin of the radar image coordinate system is set at the upper left corner of the slope radar imaging image, the abscissa x increases from left to right along the horizontal direction, and the ordinate y increases from top to bottom along the plumb direction.

[0028] The echo signal of the corner reflector in the slope radar imaging image is stronger than the echo signal of the slope surface in the slope radar imaging image, so that the pixel value of the corner reflector in the slope radar imaging image is greater than the pixel value corresponding to the slope rock surface in the slope radar imaging image. Therefore, in the slope radar imaging image, the position of the corner reflector will appear as a very bright point.

[0029] Perform wave intensity filtering on the slope radar imaging image, collect the pixel value corresponding to each pixel point in the slope radar imaging image after wave intensity filtering, filter out the pixel points based on the pixel value, and determine the image coordinates of the filtered pixel points in the radar image coordinate system of the slope radar imaging image .

[0030] In order to present the slope vision in the video image to the maximum extent, a slope video monitoring device is set up next to the slope radar to record and observe the real-time change status of the slope. The video monitoring is set to 1x, a frame of the video stream is intercepted, and the image coordinates of the corner reflector in the frame are manually marked. .

[0031] Since the image resolution of the slope radar image is m×n pixels, and the image resolution of the slope video surveillance image is o×p pixels, and since the slope radar RF transmitting front end and the central optical axis of the video image cannot coincide, if there is a point in the radar image , then its coordinates in the video image cannot be , that is, there is a certain deviation in the distribution of imaging pixels of the same target slope between slope radar and video surveillance.

[0032] This embodiment uses an affine transformation matrix to correct the coordinates of the slope radar imaging image, and accurately fits the imaging pixels of the slope radar imaging image and the slope video monitoring image after correction.

[0033] In this embodiment, the coordinates of the corner reflectors in the slope radar imaging image and the slope video monitoring image are respectively and The affine transformation matrix is ​​determined, and the affine transformation matrix establishes a one-to-one correspondence between the slope radar imaging image and the slope video monitoring image.

[0034] Step 400: Establish an affine transformation matrix between the slope radar imaging image and the slope video monitoring image so that the image coordinate value of the corner reflector in the image coordinate system is Image coordinates of the corner reflector in the video image coordinate system There is a one-to-one correspondence between them.

[0035] In step 400, the implementation method of establishing the affine transformation matrix between the slope radar imaging image and the slope video monitoring image is: Using the slope video surveillance image as the base map, the slope radar imaging image is mapped to the slope video surveillance image through the affine transformation matrix, and the pixel coordinates of the slope radar imaging image after the affine transformation of the affine transformation matrix match the pixel coordinates on the slope video surveillance image one by one; Among them, the expression of the affine transformation matrix is: ; is the coordinate of the slope radar image after affine transformation by the affine transformation matrix; is the coordinate of the slope radar image before affine transformation; is the affine transformation matrix, where , , , , and are the affine transformation parameters.

[0036] The implementation method of mapping the slope radar imaging image to the slope video monitoring image through the affine transformation matrix is: Input the coordinate values ​​of each corner reflector in the slope radar imaging image and the slope video monitoring image to obtain the affine transformation matrix , , , , and .

[0037] The slope radar imaging image, affine transformation matrix and the size of the output image are input into the Python software. The pixel coordinates of the slope radar imaging image after the affine transformation matrix are exactly the same as the coordinates of the same pixel points on the slope video surveillance image.

[0038] Specifically, the affine transformation matrix can be calculated using the cv2.estimateAffine2D() function of the Python OpenCV software library. The specific implementation method is as follows: input the coordinate values ​​of multiple corner reflectors in the slope radar imaging image and the slope video monitoring image, and output , , , , and , forming an affine transformation matrix .

[0039] Then use the cv2.warpAffine() function to implement the affine transformation of the image. Specifically, input the slope radar imaging image, the affine transformation matrix, the size of the output image, and output the slope radar imaging image after affine transformation, such as Figure 4 and Figure 5 As shown, Figure 4 is the slope radar image before affine transformation, Figure 5 This is the slope radar image after affine transformation.

[0040] Step 500: Synchronize and fit the slope radar imaging image with the 1x slope video stream based on the affine transformation matrix, determine the position of the target query point in the slope video surveillance image at different magnifications in the 1x slope video surveillance image, and obtain the radar monitoring data corresponding to the target query point in the slope video surveillance image at different magnifications in the slope radar imaging image.

[0041] The implementation method of synchronously fitting the slope radar imaging image with the 1-time slope video stream based on the affine transformation matrix is: traverse all pixel points on the slope radar imaging image one by one, and obtain the coordinate value corresponding to each pixel point based on the image coordinate system.

[0042] After the coordinate value of each pixel point on the slope radar imaging image is converted through the affine transformation matrix, it is the same as the coordinate value of the same pixel point on the slope video monitoring image, so that the slope radar imaging image is transformed into a slope radar monitoring cloud map that matches the pixel points of the slope video monitoring image one by one. The slope radar imaging image is synchronously fitted with the 1x slope video stream as shown in the figure. Figure 6 As shown in the figure, the slope video monitoring image is used as the base map, and the slope radar monitoring image is used as the cloud map. Figure 7 shown.

[0043] This implementation method first constructs an affine transformation matrix using the corner reflectors on the slope radar imaging image as multiple control points, and then the other pixel points on the slope radar imaging image are transformed in sequence based on the affine transformation matrix established based on the "multiple control points", and finally forms a slope radar imaging image after affine transformation. The transformed slope radar imaging image has the same coordinate value as the same pixel point on the slope video surveillance image.

[0044] In actual application, it is impossible for the slope video surveillance image to maintain 1 magnification all the time. In order to observe the slope rock surface more clearly, it is necessary to adjust the camera pan (the direction of the optical axis center) and the video magnification M. The radar monitoring data corresponding to the target query point of the slope video surveillance image at different magnifications is obtained in the following way: First, determine the position of the target query point in the slope video surveillance image with different magnifications in the slope video surveillance image with 1 magnification. The principle diagram of pixel positioning of different magnification images is as follows: Figure 8 shown.

[0045] Based on the position of the target query point in the 1-magnification slope video monitoring image, the position of the target query point in the slope radar imaging image after affine transformation is determined, thereby obtaining the radar monitoring data corresponding to the target query point in the slope radar imaging image.

[0046] The method for determining the position of the target query point in the slope video surveillance image with different magnifications in the slope video surveillance image with 1 magnification is as follows: ; in, is the image plane coordinates of the target query point in the slope video monitoring images with different magnifications in the 1-magnification image; is the image plane coordinate of the optical axis center of the slope video monitoring image with different magnifications in the 1-magnification image; are the image plane coordinates of the target query point in the slope video surveillance images at different magnifications; M is the video image magnification.

[0047] This implementation method performs zone monitoring on the video and radar monitoring operations of the open-pit mine, divides the open-pit mine into multiple plane blocks, installs slope radars and video monitoring equipment in opposite directions of each plane block, thereby realizing radar monitoring and video monitoring of each plane block. Since the video stream is transmitted and updated in real time, time consumption is not considered, and the radar monitoring data and video monitoring data are two-dimensionally fitted, there is no three-dimensional modeling problem, there is no requirement for computer performance, and time consumption is not considered.

[0048] When fitting the video surveillance images and radar monitoring data of each plane block, a frame of image is captured from the video stream, and then a radar imaging image is obtained. The affine transformation matrix of the two images can be solved using the Python opencv software library. The subsequent imaging images generated by the radar can be transformed using this affine transformation matrix. The total time taken is no more than 5 minutes, which can greatly reduce the time taken to fit the video surveillance images and radar monitoring data of the mine, and realize real-time updating of the video surveillance base map.

[0049] This embodiment performs radar monitoring and video monitoring of the slope, and displays the slope displacement monitoring data contained in the slope radar imaging image in the slope video monitoring image, thereby realizing real-time updating of the slope video monitoring base map, significantly improving the visualization effect of the slope radar monitoring data, improving the real-time and accuracy of monitoring, and providing more intuitive and effective technical support for slope monitoring and early warning.

[0050] The above embodiments are only exemplary embodiments of the present application and are not intended to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and protection scope of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present application.

Claims

1. A method for displaying slope radar monitoring data and video images, characterized in that: The following steps are involved: Step 100: Divide the open-pit mine into different monitoring areas, arrange multiple corner reflectors on the slope surface of each monitoring area, and install corresponding slope radar and video monitoring equipment opposite to each monitoring area; Step 200: construct a radar image coordinate system of the slope radar image of the monitoring area, determine the position of the corner reflector in the slope radar image based on the strength of the echo signal in the slope radar image, and determine the image coordinate value of the corner reflector through the image coordinate system ; Step 300: intercept the slope video monitoring image from the slope video stream in the monitoring area, construct the video image coordinate system, and manually mark the image coordinate value of the corner reflector in the slope video monitoring image frame. ; Step 400: Establish an affine transformation matrix between the slope radar imaging image and the slope video monitoring image so that the image coordinate value of the corner reflector in the image coordinate system is The image coordinate value of the corner reflector in the video image coordinate system There is a one-to-one correspondence between them; Step 500: Synchronously fit the slope radar imaging image with the 1-magnification slope video stream based on the affine transformation matrix, and determine the position of the target query point in the slope video surveillance image at different magnifications in the 1-magnification slope video surveillance image, so as to perform thumbnail fit of the slope video surveillance images at different magnifications with the slope radar imaging image.

2. The method for displaying slope radar monitoring data and video images according to claim 1, characterized in that: In step 100, all corner reflectors are evenly dispersed on the slope surface, the number of corner reflectors arranged on the slope surface is at least 3, and each reflective surface of each corner reflector is unobstructed.

3. The method for displaying slope radar monitoring data and video images according to claim 1, characterized in that: In step 200, the radar image coordinate system is used to describe the coordinate system of each pixel position in the slope radar imaging image, and the origin of the radar image coordinate system is set at the upper left corner of the slope radar imaging image; The echo signal of the corner reflector in the slope radar imaging image is stronger than the echo signal of the slope surface in the slope radar imaging image, so that the pixel value of the corner reflector in the slope radar imaging image is greater than the pixel value corresponding to the slope rock surface in the slope radar imaging image.

4. The method for displaying slope radar monitoring data and video images according to claim 3, characterized in that: The image resolution of the slope radar imaging image is m×n pixels, the slope radar imaging image is subjected to wave intensity filtering, the pixel value corresponding to each pixel point in the slope radar imaging image after wave intensity filtering is collected, the pixel points are screened out based on the pixel values, and the image coordinates of the screened pixel points in the radar image coordinate system of the slope radar imaging image are determined .

5. The method for displaying slope radar monitoring data and video images according to claim 4, characterized in that: In step 300, the image resolution of the slope video monitoring image is o×p pixels.

6. The method for displaying slope radar monitoring data and video images according to claim 5, characterized in that: In step 400, the method for establishing the affine transformation matrix between the slope radar imaging image and the slope video monitoring image is: Using the slope video surveillance image as a base map, the slope radar imaging image is mapped to the slope video surveillance image through an affine transformation matrix, and the pixel coordinates of the slope radar imaging image after affine transformation by the affine transformation matrix are matched one by one with the pixel coordinates on the slope video surveillance image; Among them, the expression of the affine transformation matrix is: ; The coordinates of the slope radar image after affine transformation by the affine transformation matrix; are the coordinates of the slope radar image before affine transformation; is the affine transformation matrix, where , , , , and are the affine transformation parameters.

7. The method for displaying slope radar monitoring data and video images according to claim 6, characterized in that: The implementation method of mapping the slope radar imaging image to the slope video monitoring image through an affine transformation matrix is: Input the coordinate values ​​of each corner reflector in the slope radar imaging image and the slope video monitoring image to obtain the affine transformation matrix , , , , and ; The slope radar imaging image, affine transformation matrix and the size of the output image are input into the Python software. The pixel coordinates of the slope radar imaging image after the affine transformation matrix are identical to the coordinates of the same pixel points on the slope video surveillance image.

8. The method for displaying slope radar monitoring data and video images according to claim 7, characterized in that: Traversing all pixel points on the slope radar imaging image one by one, and obtaining the coordinate value corresponding to each pixel point based on the image coordinate system; After the coordinate value of each pixel point on the slope radar imaging image is converted through the affine transformation matrix, it is the same as the coordinate value of the same pixel point on the slope video surveillance image, so that the slope radar imaging image is transformed into a slope radar monitoring cloud map that matches the pixel points of the slope video surveillance image one by one.

9. The method for displaying slope radar monitoring data and video images according to claim 7, characterized in that: The implementation method of obtaining the radar monitoring data corresponding to the slope radar imaging image of the target query point of the slope video monitoring image at different magnifications is as follows: First, determine the position of the target query point in the slope video monitoring image with different magnifications in the slope video monitoring image with 1 magnification; Based on the position of the target query point in the 1-magnification slope video monitoring image, the position of the target query point corresponding to the slope radar imaging image after affine transformation is determined, thereby obtaining the radar monitoring data corresponding to the target query point in the slope radar imaging image.

10. The method for displaying slope radar monitoring data and video images according to claim 9, characterized in that: The method for determining the position of the target query point in the slope video surveillance image with different magnifications in the slope video surveillance image with 1 magnification is as follows: ； in, is the image plane coordinates of the target query point in the slope video monitoring image with different magnifications in the 1-magnification image; are the image plane coordinates of the optical axis center of the slope video monitoring image with different magnifications in the 1-magnification image; are respectively the image plane coordinates of the target query point in the slope video monitoring image at different magnifications; M is the video image magnification.

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