A slope radar data accurate visualization method, readable storage medium and device

Abstract

The present application relates to the technical field of geological disaster monitoring and early warning, and in particular to a slope radar data accurate visualization method, a readable storage medium and equipment. The method comprises the following steps: obtaining a data set by using a radar; performing data preprocessing; converting three-dimensional terrain point coordinate values to a two-dimensional polar coordinate space to obtain polar coordinates corresponding to the three-dimensional terrain points; matching the slope radar resolution unit with the three-dimensional terrain points, and calculating the three-dimensional space coordinates corresponding to the slope radar resolution unit. The method of the present application maps three-dimensional space to polar coordinates, preliminarily screens the three-dimensional terrain points near the slope radar resolution unit in combination with a buffer zone, then secondarily screens the nearest three-dimensional terrain points in the four directions of up, down, left and right, and finally estimates the accurate three-dimensional space coordinates of the slope radar resolution unit by using the inverse distance weighted interpolation method, thereby realizing one-to-one correspondence between the radar monitoring data two-dimensional polar coordinates and the three-dimensional space coordinates, accurate mapping, and providing a basis for subsequent data visualization and monitoring and early warning analysis.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geological disaster monitoring and early warning, and particularly relates to a slope radar data accurate visualization method, a readable storage medium and equipment. BACKGROUND

[0002] With the development of remote sensing technology, slope radar and laser radar technology have been widely used in the field of geological disaster monitoring and early warning. In actual use, the data obtained by the slope radar is usually two-dimensional polar coordinate data, which needs to be displayed on a three-dimensional geographic space so as to better visualize the slope radar data and analyze the disaster.

[0003] At present, the data of ground-based synthetic aperture radar (slope radar) is two-dimensional polar coordinate data, which is composed of two dimensions of (r, θ), wherein r is the distance in three-dimensional space, and θ is the plane rotation angle. Since the vertical rotation angle φ is lacking, the data of the ground-based radar cannot be converted to three-dimensional space, and the conversion process of the two-dimensional data (r, θ) of the ground-based radar to three-dimensional space (x, y, z) is nonlinear calculation. Therefore, it is impossible to simply realize one-to-one correspondence between the slope radar data and the three-dimensional terrain points.

[0004] The existing technology generally directly uses the two-dimensional polar coordinate mode to display the monitoring data of the slope radar, or sets a target (corner reflector) in the monitoring site, measures the three-dimensional geographic space coordinates of the target, and then finds the corresponding radar data according to the transmission signal of the target, so as to visualize the corresponding three-dimensional space coordinates. In addition, some algorithms normalize the point cloud data of the three-dimensional laser radar to the two-dimensional polar coordinate space of the slope radar, and then establish the corresponding relationship between the point cloud and the resolution unit of the slope radar, so as to realize the three-dimensional visualization of the radar monitoring data. Although this method realizes the three-dimensional display of the radar monitoring data by establishing the corresponding relationship between the three-dimensional point cloud and the two-dimensional resolution unit of the slope radar, the calculation efficiency is relatively low due to the large amount of data of the three-dimensional point cloud. Moreover, since the terrain data obtained by the three-dimensional laser radar is discrete, the calculation result is a rough correspondence, and the three-dimensional rectangular coordinate values of the resolution unit of the slope radar in the three-dimensional geographic space are not accurately calculated. In the subsequent calculation of the boundary and area of the large deformation area, it is difficult to obtain accurate results, which not only affects the speed of visualization, but also affects the early warning analysis. The methods of directly displaying the two-dimensional polar coordinate data or displaying the monitoring data of a limited target fail to take advantage of the massive data of the slope radar, and the display effect is not intuitive enough.

[0005] In summary, there is an urgent need for a method capable of quickly and accurately converting radar two-dimensional polar coordinate data into three-dimensional geographic space coordinate data to solve the problems in the prior art. SUMMARY

[0006] The application aims to provide a slope radar data accurate visualization method, readable storage medium and equipment capable of realizing fast and accurate conversion of radar two-dimensional polar coordinate data into three-dimensional geographic spatial coordinate data, and the specific technical solutions are as follows.

[0007] A slope radar data accurate visualization method comprises the following steps:

[0008] Step one, acquiring a data set by using a radar;

[0009] Step two, performing data preprocessing on the data set obtained in step one to obtain three-dimensional terrain point coordinate values;

[0010] Step three, converting the three-dimensional terrain point coordinate values obtained in step two to a two-dimensional polar coordinate space to obtain polar coordinates (r c , θ c ) corresponding to the three-dimensional terrain points;

[0011] Step four, matching the slope radar resolution unit and the three-dimensional terrain point to calculate the three-dimensional spatial coordinates corresponding to the slope radar resolution unit, and the matching specifically comprises:

[0012] Step S4.1, setting the coordinates of the slope radar resolution unit as (r target , θ target ), and preliminarily screening out points pts1 near the slope radar resolution unit from the polar coordinates (r c , θ c ) of the three-dimensional terrain points obtained in step three, and the following formula is satisfied:

[0013] r δ ≤|r c -r target | and θ δ ≤|θ c -θ target |;

[0014] wherein, r δ , θ δ are the size of the buffer zone, r δ ≥2×RngRes, θ δ ≥2×AngRes, RngRes is the distance resolution of the slope radar, and AngRes is the angle resolution of the slope radar;

[0015] Step S4.2, finding the nearest neighbor points pt1, pt2, pt3 and pt4 above, below, left and right of the slope radar resolution unit from the preliminarily screened points pts1;

[0016] Step S4.3, using the inverse distance weighted interpolation method according to the four points pt1, pt2, pt3 and pt4 selected in step S4.2 to calculate the three-dimensional spatial coordinates (r target , θ δ ) of the slope radar resolution unit (r target , θ target ).target θ target The corresponding three-dimensional spatial coordinates (x) target ,y target , z target ).

[0017] Preferably, step S4.2 includes:

[0018] Filter from pts1 to satisfy θ c -θ target Point set pts >0 up Then from pts up Calculate the distance (r) point by point target θ target The nearest point, i.e. The smallest point pt1 has two-dimensional polar coordinates (r1, θ1) and three-dimensional spatial coordinates (x1, y1, z1).

[0019] Filter from pts1 to satisfy θ c -θ target Point set pts ≤ 0 down Then from pts down Calculate the distance (r) point by point target θ target The nearest point, i.e. The smallest point pt2 has two-dimensional polar coordinates (r2, θ2) and three-dimensional spatial coordinates (x2, y2, z2).

[0020] Filter from pts1 to satisfy r c -r target Point set pts > 0 right Then from pts right Calculate the distance (r) point by point target θ target The nearest point, i.e. The smallest point pt3 ​​has two-dimensional polar coordinates (r3, θ3) and three-dimensional spatial coordinates (x3, y3, z3).

[0021] Filter from pts1 to satisfy r c -r target Point set pts ≤ 0 left Then from pts left Calculate the distance (r) point by point target θ target The nearest point, i.e. The smallest point pt4 has two-dimensional polar coordinates (r4, θ4) and three-dimensional spatial coordinates (x4, y4, z4).

[0022] Preferably, in step S4.3, the three-dimensional spatial coordinates (x)target , y target , z target ) are as follows:

[0023]

[0024] wherein: 1≤i≤4; ω is a weight, the weight function γ i = |θ i - θ target |, and α and β are weight factors of distance and angle respectively, α≥1, 0.01≤β≤0.5.

[0025] Preferably, in the step two, the three-dimensional coordinates of the point P1 where the slope radar itself is located are (x r , y r , z r ); the three-dimensional coordinates of the angle starting point P2 of the slope radar are (x s , y s , z s ), and the angle θ of the slope radar is the angle of clockwise rotation, and the value range of θ is [0, 2π].

[0026] Preferably, in the step three:

[0027] Let the coordinates of the three-dimensional terrain point P3 be (x c , y c , z c );

[0028] Then the polar coordinates (r c , θ c ) corresponding to the three-dimensional terrain point P3 are calculated as follows:

[0029]

[0030] wherein: the vector the vector P1P2·P1P3 is the dot product of the vectors and , P1P2·P1P3=(x s -x r )(x c -x r )+(y s -y r )(y c -y r ); |P1P2| and |P1P3| are the norms of the vectors and , P1P2×P1P3 is the cross product of the vectors​ and the outer product of P1P2 and P1P3, P1P2 x P1P3 = (x s -x r )(y c -y r )-(y s -y r )(x c -x r ).

[0031] The technical scheme of the present application has the beneficial effects that the slope radar data precision visualization method disclosed by the present application comprises the following steps: obtaining a data set by using a laser radar; performing data preprocessing to obtain three-dimensional terrain point coordinate values; converting the obtained three-dimensional terrain point coordinate values to a two-dimensional polar coordinate space to obtain polar coordinates corresponding to the three-dimensional terrain points; matching a slope radar resolution unit with the three-dimensional terrain points to calculate three-dimensional space coordinates corresponding to the slope radar resolution unit. The scheme of the present application maps three-dimensional space to polar coordinates, preliminarily screens the three-dimensional terrain points near the slope radar resolution unit in combination with a buffer area, then secondarily screens the nearest three-dimensional terrain points in four directions of up, down, left and right, and finally estimates the precise three-dimensional space coordinates of the slope radar resolution unit by using an inverse distance weighted interpolation method, thereby realizing one-to-one correspondence between the radar monitoring data two-dimensional polar coordinates and the three-dimensional space coordinates, precise mapping, and providing a basis for subsequent data visualization and monitoring and early warning analysis.

[0032] The present application further discloses a readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the above-mentioned slope radar data precision visualization method.

[0033] The present application further discloses a device comprising a processor and a memory for storing executable instructions of the processor, wherein the processor is configured to execute the above-mentioned slope radar data precision visualization method by executing the executable instructions.

[0034] In addition to the objects, features and advantages described above, the present application has other objects, features and advantages. The present application will be further described in detail with reference to the embodiments. DETAILED DESCRIPTION

[0035] The embodiments of the present application will be described in detail below, but the present application can be implemented in various different ways as limited and covered by the claims.

[0036] Embodiment:

[0037] A slope radar data precision visualization method specifically comprises the following steps:

[0038] Step one, obtaining a data set by using a slope radar;

[0039] In this embodiment, the three-dimensional geographic coordinates (x, y, z, r, g, b) collected by the device such as laser radar, (x, y, z) is the three-dimensional spatial coordinates of the terrain point, (r, g, b) is the color value corresponding to the terrain point.

[0040] Step two, the data set obtained in step one is preprocessed to obtain three-dimensional terrain point coordinate values.

[0041] In this embodiment: read the slope radar data parameters, set the three-dimensional coordinates of the point P1 where the slope radar itself is located as (x r , y r , z r ), the distance resolution of the slope radar is RngRes, the angle resolution of the slope radar is AngRes, the three-dimensional coordinates of the angle starting point P2 of the slope radar are (x s , y s , z s ), and the angle θ of the slope radar is the angle of clockwise rotation, and the value range of θ is [0, 2π].

[0042] Step three, convert the three-dimensional terrain point coordinate values obtained in step two to two-dimensional polar coordinate space to obtain the polar coordinates (r c , θ c ) corresponding to the three-dimensional terrain point, specifically:

[0043] Let the coordinates of the three-dimensional terrain point P3 be (x c , y c , z c );

[0044] Then the polar coordinates (r c , θ c ) corresponding to the three-dimensional terrain point P3 are calculated as follows:

[0045]

[0046] Where: vector vector P1P2·P1P3 is the dot product of vectors and , P1P2·P1P3 = (x s -x r )(x c -x r )+(y s -y r )(y c -y r ); |P1P2| and |P1P3| are the modules of vectors and ,​ P1P2×P1P3 is the outer product of vectors and , P1P2×P1P3 = (x s -x r )(y c -y r )-(y s -y r )(x c -x r ).

[0047] Step four, the slope radar resolution unit is matched with the three-dimensional terrain point, and the three-dimensional space coordinates corresponding to the slope radar resolution unit are calculated, which specifically includes:

[0048] Step S4.1, the coordinates of the slope radar resolution unit are set as (r target , θ target ), and the points pts1 near the slope radar resolution unit are preliminarily screened out from the three-dimensional terrain points corresponding to the polar coordinates (r c , θ c ) obtained in step three, which satisfy the following formula:

[0049] r δ ≤|r c -r target | and θ δ ≤|θ c -θ target |;

[0050] Wherein: r δ , θ δ are the size of the buffer zone, r δ ≥2×RngRes, θ δ ≥2×AngRes;

[0051] Step S4.2, find the nearest neighbor points pt1, pt2, pt3 and pt4 above and below and left and right of the target resolution unit from the preliminarily screened pts1, and the detailed operation is:

[0052] Screen the point set pts up from pts1 that satisfies θ c -θ target >0, and then calculate the distance (r target , θ target ) of each point in pts up to find the nearest point, that is the smallest point pt1, the two-dimensional polar coordinates corresponding to which are (r1, θ1), and the three-dimensional space coordinates are (x1, y1, z1);

[0053] Screen the point set pts1 from pts1 that satisfies θc -θ target Point set pts ≤ 0 down Then from pts down Calculate the distance (r) point by point target θ target The nearest point, i.e. The smallest point pt2 has two-dimensional polar coordinates (r2, θ2) and three-dimensional spatial coordinates (x2, y2, z2).

[0054] Filter from pts1 to satisfy r c -r target Point set pts > 0 right Then from pts right Calculate the distance (r) point by point target θ target The nearest point, i.e. The smallest point pt3 ​​has two-dimensional polar coordinates (r3, θ3) and three-dimensional spatial coordinates (x3, y3, z3).

[0055] Filter from pts1 to satisfy r c -r target Point set pts ≤ 0 left Then from pts left Calculate the distance (r) point by point target θ target The nearest point, i.e. The smallest point pt4 has two-dimensional polar coordinates (r4, θ4) and three-dimensional spatial coordinates (x4, y4, z4).

[0056] Step S4.3: Using the inverse range weighted interpolation method, calculate the slope radar resolution unit (r) based on the four points pt1, pt2, pt3, and pt4 selected in step S4.2. target θ target The corresponding three-dimensional spatial coordinates (x) target y target , z target The details are as follows:

[0057]

[0058] Where: 1≤i≤4; ω is the weight, and the weight function is... d i =|r i -r target |,γ i =|θ i -θ target|, a and β are weight factors of distance and angle respectively, used to control the strength of weighting. In this embodiment: a determines the influence of distance in weight calculation, a≥1, the closer the point, the greater the weight; β is used to adjust the influence of angle difference in interpolation calculation, 0.01≤β≤0.5.

[0059] The technical scheme of the embodiment is applied, specifically:

[0060] The key of the scheme of the embodiment is to effectively and accurately align the two-dimensional polar coordinate data of the radar with the three-dimensional terrain data, and to estimate the accurate three-dimensional space coordinates of the radar resolution unit of the slope by using a suitable interpolation method. The method proposed in the embodiment is simple and easy to implement, and has high accuracy. Through three-dimensional space mapping to polar coordinates, the three-dimensional terrain points near the radar resolution unit of the slope are preliminarily screened in combination with the buffer area, then the nearest three-dimensional terrain points in the four directions of up, down, left and right are screened again, and finally the accurate three-dimensional space coordinates of the radar resolution unit of the slope are estimated by the inverse distance weighted interpolation method. The one-to-one correspondence between the two-dimensional polar coordinates of the radar monitoring data and the three-dimensional space coordinates is realized, accurate mapping is realized, and a basis is provided for subsequent data visualization and monitoring and early warning analysis.

[0061] The embodiment also discloses a readable storage medium having a computer program stored thereon, and the computer program is executed by a processor to realize the accurate visualization method of slope radar data.

[0062] The embodiment also discloses a device, including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the accurate visualization method of slope radar data by executing the executable instructions.

[0063] The above only describes the preferred embodiments of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for precise visualization of slope radar data, characterized in that, Includes the following steps: Step 1: Use radar to acquire the dataset; Step 2: Preprocess the dataset obtained in Step 1 to obtain the coordinate values ​​of three-dimensional terrain points; Step 3: Based on the 3D terrain point coordinates obtained in Step 2, convert them to 2D polar coordinate space to obtain the corresponding polar coordinates (r) of the 3D terrain points. c ,θ c ); Step 4: Match the slope radar resolution unit with the 3D terrain points to calculate the corresponding 3D spatial coordinates of the slope radar resolution unit. This includes: Step S4.1: Let the coordinates of the slope radar resolution unit be (r target ,θ target ), from the polar coordinates (r) corresponding to the three-dimensional terrain points obtained in step three c ,θ c In the preliminary screening, points pts1 near the slope radar resolution unit are selected, satisfying the following formula: r δ ≤|r c -r target |and the δ ≤|θ c -θ target |; Where: r δ θ δ r is the size of the buffer. δ ≥2×RngRes, θ δ ≥2×AngRes, where RngRes is the range resolution of the slope radar and AngRes is the angular resolution of the slope radar; Step S4.2: Find the nearest neighbor points pt1, pt2, pt3 and pt4 of the target resolution unit in the top, bottom and left and right directions from the initially screened pts1; Step S4.3: Using the inverse range weighted interpolation method, calculate the slope radar resolution unit (r) based on the four points pt1, pt2, pt3, and pt4 selected in step S4.

2. target ,θ target The corresponding three-dimensional spatial coordinates (x) target ,y target ,z target ).

2. The method for precise visualization of slope radar data according to claim 1, characterized in that, Step S4.2 includes: Filter from pts1 to satisfy θ c -θ target Point set pts >0 up Then from pts up Calculate the distance (r) point by point target ,θ target The nearest point, i.e. The smallest point pt1 has two-dimensional polar coordinates (r1, θ1) and three-dimensional spatial coordinates (x1, y1, z1). Filter from pts1 to satisfy θ c -θ target Point set pts ≤ 0 down Then from pts down Calculate the distance (r) point by point target ,θ target The nearest point, i.e. The smallest point pt2 has two-dimensional polar coordinates (r2, θ2) and three-dimensional spatial coordinates (x2, y2, z2). Filter from pts1 to satisfy r c -r target Point set pts >0 right Then from pts right Calculate the distance (r) point by point target ,θ target The nearest point, i.e. The smallest point pt3 ​​has two-dimensional polar coordinates (r3, θ3) and three-dimensional spatial coordinates (x3, y3, z3). Filter from pts1 to satisfy r c -r target Point set pts ≤ 0 left Then from pts left Calculate the distance (r) point by point target ,θ target The nearest point, i.e. The smallest point pt4 has two-dimensional polar coordinates (r4, θ4) and three-dimensional spatial coordinates (x4, y4, z4).

3. The method for precise visualization of slope radar data according to claim 2, characterized in that, In step S4.3, the three-dimensional spatial coordinates (x) target ,y target ,z target The details are as follows: Where: 1≤i≤4; ω is the weight, and the weight function is... d i =|r i -r target |,γ i =|θ i -θ target |, where α and β are the weighting factors for distance and angle, respectively, α≥1, 0.01≤β≤0.

5.

4. A method for precise visualization of slope radar data according to any one of claims 1-3, characterized in that, In step two: the three-dimensional coordinates of point P1 where the slope radar is located are (x... r ,y r ,z r ); the three-dimensional coordinates (x, y) of the starting point P2 of the slope radar angle. s ,y s ,z s The angle θ of the slope radar is... The angle of clockwise rotation, θ, ranges from [0, 2π].

5. The method for precise visualization of slope radar data according to claim 4, characterized in that, In step three: Let the coordinates of the three-dimensional terrain point P3 be (x... c ,y c ,z c ); Then the polar coordinates (r) corresponding to the three-dimensional terrain point P3 c ,θ c The following formula is used for calculation: Where: vector vector P1P2·P1P3 are vectors and The dot product, P1P2·P1P3=(x s -x r (x) c -x r )+(y s -y r )(y c -y r |P1P2| and |P1P3| are vectors respectively. and The model, P1P2×P1P3 is a vector and The outer product, P1P2×P1P3=(x s -x r )(y c -y r )-(y s -y r (x) c -x r ).

6. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the slope radar data precise visualization method according to any one of claims 1-5.

7. A device, characterized in that, include: processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the slope radar data precision visualization method as described in any one of claims 1-5 by executing the executable instructions.

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