A method for inverting wind profiles in target areas using ground-based lidar

Abstract

The present invention relates to an inversion method, specifically a method for inverting the wind profile of a target area using a ground-based laser radar. The method comprises the following steps: Step 1: Calculating the elevation and azimuth ranges of the radar beam required for scanning based on the coordinate relationship between the radar and the target location in a geographic coordinate system; Step 2: The radar performs a three-dimensional volume scan of the target detection area according to the azimuth and elevation angle ranges calculated in Step 1, obtaining radial wind speed data for each range unit of each laser beam; and Step 3: Inverting the data obtained from the scanned detection to generate and output wind profile data for the target area. The present invention has the beneficial effects of effectively improving the wind profile detection performance of the laser radar and enabling long-range wind profile detection.

Description

Technical Field

[0001] The present invention relates to an inversion method, and in particular to an inversion method for a ground-based laser radar target area wind profile. Background Art

[0002] As we all know, wind profile inversion is one of the most important applications of laser wind radar. Commonly used wind profile inversion methods include the following:

[0003] (1) Range and Azimuth Display (VAD) method: The core of this method is to assume that the actual wind field changes linearly on the same height plane. Under this assumption, the radial velocity V observed by the radar is h On a range circle (data with the same elevation angle and radial distance, but different azimuths) is the trigonometric function of the azimuth angle θ:

[0004] V h =ucosθsinγ+v sinθsinγ+w cosγ

[0005] By selecting data on a certain distance circle for calculation, the horizontal wind speed can be obtained, and then by calculating the data on distance circles at different heights, the wind profile data above the radar can be obtained.

[0006] (2) Doppler beam swinging (DBS): The lidar performs four-beam scanning in the east, south, west, and north directions around the scanning axis. The azimuth interval of each beam is 90°, and adjacent beams are orthogonal to each other according to the following formula:

[0007]

[0008] The wind profile data above the radar can be obtained. This method has been widely used due to its advantages such as small amount of calculation and simple calculation.

[0009] Subsequently, various wind field inversion methods such as VAP, VVP, and NVAD appeared, but these methods only detect the wind profile above the radar, such as Figure 1 ), it is impossible to detect wind profiles for target areas within tens of kilometers.

[0010] However, in areas inaccessible to humans, such as natural wind resource mapping, precise target area wind detection, wind field support for artillery impact zones, aerospace system landing wind field support, and airdrops, existing wind profile inversion strategies are ineffective due to the inability to place radar on the ground below the target airspace. Therefore, there is an urgent need for long-range wind profile detection.

[0011] The coordinate system related to this project is defined as follows:

[0012] Geographic coordinate system refers to the WGS-84 World Geodetic Coordinate System. Its geometric meaning is that the coordinate origin is the center of mass of the earth, the Z axis of its geocentric rectangular coordinate system points to the direction of the earth's pole (CTP), the X axis points to the intersection of the zero meridian plane and the CTP equator, and the Y axis is perpendicular to the Z axis and the X axis to form a right-handed coordinate system, such as Figure 9 shown.

[0013] The radar coordinate system refers to the radar position as the origin, the X axis points to the east, the Y axis points to the north, and the Z axis points to the zenith. Figure 10 shown.

[0014] The definitions of terms related to the present invention are as follows:

[0015] Radial wind speed: refers to the wind speed along the direction of the laser beam. Summary of the Invention

[0016] The purpose of the present invention is to provide a target area lidar wind profile inversion method in view of the defects of the prior art.

[0017] In order to achieve the above-mentioned object, the present invention provides a target area wind profile inversion algorithm based on a ground-based laser radar. The specific technical solution adopted by the present invention is as follows: A target area wind profile inversion method of a ground-based laser radar comprises:

[0018] Step 1: Calculate the elevation and azimuth ranges that the radar beam needs to scan based on the coordinate relationship between the radar and the target in the geographic coordinate system.

[0019] Step 2: The radar performs a three-dimensional volume scan of the target detection area according to the azimuth and elevation angle ranges calculated in step 1, and obtains radial wind speed data for each range unit of each laser beam;

[0020] Step 3: Invert the data obtained from the scanning detection to form the wind profile data of the target area and output it.

[0021] The above-mentioned target area lidar wind profile inversion method, wherein said step 1 includes

[0022] Step 1.1, based on the geographic coordinate system, the coordinates of the radar 1 position are O(Lg1, La1, H1), the coordinates of the detection target position 2 are P(Lg2, La2, H2), and the target area is the detection airspace 3, where Lgi is the longitude, Lai is the latitude, and Hi is the altitude (where i = 1, 2). The detection area of ​​airspace 3 is approximately a cylinder S, and the coordinates of the central axis of the cylinder S on the ground are (Lg2, La2, H2), the radius of the cylinder is R, and the height resolution is h0.

[0023] Step 1.2: Divide the target area into corresponding grid points according to the target area wind profile detection altitude resolution. The grid points are divided into cubes. The cube area centered at the target position altitude is included in the altitude layer. Taking any detection altitude h as an example, the detection area at altitude layer h is a cylindrical sub-area with a height of h0 on the cylinder S, recorded as S h , S h The altitude of the lower surface is S h The altitude of the upper base is

[0024] Step 1.3, for cylinder S h For example, the cylindrical section at height h is denoted as g, and the line connecting the center of radar 1 and g is denoted as m. The theory of spatial solid geometry is used to solve the diameter l0 in plane g that is parallel to the normal vector of line m.

[0025] Divide the diameter l0 into four equal parts, take the five equal points of l0, and calculate the coordinates of the five equal points in the geographic coordinate system O1(x1,y1,z1), O2(x2,y2,z2), O3(x3,y3,z3), O4(x4,y4,z4), O5(x5,y5,z5), respectively. Connect point O with O1, O2, O3, O4, O5, then the vector (where i = 1, 2, ..., 5), the laser beams are respectively along the vector (where i = 1, 2, ..., 5) and scan in the direction of

[0026] Step 1.4, through coordinate transformation, the coordinates of the laser beam are transformed from the geographic coordinate system to the radar coordinate system. The scanning azimuth and elevation angles in the radar coordinate system are θ i and γ i (i=1,2,…,5),

[0027] During measurement, the radar coordinates, target position coordinates, target airspace detection altitude, altitude resolution and other parameter information are input into the host computer software. The host computer software automatically calculates the scanning azimuth and pitch angles of all altitude layers in the target area, and establishes a scanning information database for all altitude layers using the two-dimensional array Coef[n][Attitude]. Among them, n represents the altitude layer, and Attitude represents the azimuth and pitch angle information of the radar scanning beam. This array is written into the initialization file when the host computer software is running.

[0028] The above-mentioned target area lidar wind profile inversion method, wherein said step 2 includes

[0029] Step 2.1: Before measuring, the radar should face north first. The radar should be controlled to perform a three-dimensional volume scan of the target detection area according to the scanning azimuth and pitch information calculated in step 1. The scanning is performed layer by layer and the process is repeated until all measurements are completed.

[0030] Step 2.2, obtain the echo time domain data of each laser beam, divide the echo time domain data into different distance units according to the distance size, and the length of the distance unit is m0, where m0 should not be greater than The digital receiver converts the radar signal from the intermediate frequency to the base frequency through Hilbert transform, and performs spectrum transformation on the signal through the joint time-frequency analysis method based on variational mode decomposition. Multiple pulse echoes are non-coherently accumulated to obtain the original power spectrum data, which is stored in the two-dimensional array R[n][gate_num], where n represents the beam number and gate_num represents the range unit number.

[0031] Step 2.3: The power spectrum data R[n][gate_num] of each distance unit is first smoothed and denoised. Then, the echo signal is modeled as a random process. By calculating the statistical characteristics of the random process such as expectation and variance, "expectation + weight coefficient × variance" is used as the adaptive threshold detection threshold. The data above the threshold is considered to be the signal envelope. The signal envelope of each distance unit is detected, and the envelope centroid is obtained using the first-order moment. The signal peak position and intensity are solved, and the Doppler frequency and radial wind speed data V are further calculated. ri .

[0032] The above-mentioned target area lidar wind profile inversion method, wherein said step 3 includes

[0033] Step 3.1: Considering the calculation accuracy and calculation scale, the number of grids is the total number of height layers N detected in the target area, and the height of the grid does not exceed the height resolution h0 of the target area.

[0034] For a specific altitude layer, the radial wind speed data of each distance unit obtained by radar scanning detection are divided into two categories. One category is the points falling within the range of the above-mentioned network grid points, that is, the coordinates of the distance unit where the radial wind is located in the geographic coordinate system fall into the grid point area of ​​the altitude layer, which is recorded as C rI The other type is the data where the coordinates of the distance unit of radial wind in the geographic coordinate system do not fall within the range of the above network grid points, which is recorded as C rO , where r = 1, 2, ..., N, represents the rth altitude layer of the target area,

[0035] Step 3.2, for each detection altitude layer in the target area, C rI There must be no less than three distance unit data within the range; if this requirement is not met, then CrO The radial wind speed data in each distance unit of the same laser beam are fitted with a recursive function curve, and the fitted curve is recorded as f.

[0036] Step 3.3, interpolate the data to the required grid points according to the fitting function f in the above steps, and the interpolated C rI becomes C' rI , solid dots represent data that fall within the grid, hollow dots represent data that do not fall within the grid, and triangles represent interpolated data.

[0037] Step 3.4, combine the coordinate information of each beam and calculate the wind vector data set C' that falls into the same altitude layer. rI , according to the following equations, the three-dimensional wind vector (u, v, w) at this altitude layer is obtained. The conjugate gradient method and constrained multivariable linear optimization problem are used to solve the equations to find the optimal solution, which can avoid the drastic change of the fitting results caused by small changes in the acquisition parameters.

[0038]

[0039] Among them, V i,h (i=1,2,…,n) represents the i-th wind speed data falling into the altitude layer h, θ i Indicates wind speed data V i,h The corresponding azimuth in the radar coordinate system, β i Indicates wind speed data V i,h The corresponding elevation angle in the radar's own coordinate system.

[0040] In order to realize the wind profile detection of the target area of ​​the ground-based lidar, the detection range of the target airspace 3 is divided into height layers according to cylinders. According to the longitude, latitude and altitude relationship between the radar 1 and the target position 2 in the geographic coordinate system, the azimuth and pitch information of the beam scanning for scanning detection by the radar is calculated, and a three-dimensional volume scan is performed on the target airspace 3. The echo time domain data of each laser beam is collected and divided into different distance units according to the distance size. The radial wind speed data of each distance unit is calculated, and then the number of radial wind speed data falling into the target height area is judged. If the number of data is less than three, the data of each distance unit of the beam are fitted and interpolated to the target height area. The conjugate gradient method and the constrained multivariable linear optimization problem are used to find the optimal solution for all the data falling into the height area after interpolation, and the wind profile data of the height area can be obtained.

[0041] Compared with the prior art, the present invention has the following beneficial effects: the ground-based lidar target area wind profile inversion method described in the present invention pre-calculates the azimuth and elevation ranges of the radar for scanning and detection according to the relationship between the radar and the target position in the geographic coordinate system, performs a three-dimensional volume scan on the target airspace in a pre-set manner, divides the echo data of each laser beam into different distance units according to the distance for processing, adopts Hilbert transform to transform the radar signal from the intermediate frequency to the fundamental frequency, calculates the radial wind speed based on the joint time-frequency analysis of variational mode decomposition, and then obtains the wind profile data of the target airspace through the network grid method by fitting interpolation, constrained multivariate linear optimization and other operations on the data falling into the corresponding grid points, thereby effectively improving the wind profile detection performance of the lidar and realizing long-range wind profile detection, such as Figure 1 As shown in the figure on the right. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 1 is a schematic diagram comparing traditional wind profile detection and wind profile detection in an embodiment of the present invention;

[0043] Figure 2 2 is a schematic diagram of wind profile detection in an embodiment of the present invention;

[0044] Figure 3 is a schematic diagram of three-dimensional volume scanning in an embodiment of the present invention;

[0045] Figure 4 is a cross-sectional view of the target area divided by grid points in an embodiment of the present invention;

[0046] Figure 5 is a cross-sectional view of the target area divided by grid points in an embodiment of the present invention;

[0047] Figure 6 is a stereogram of the grid division points of the target area in an embodiment of the present invention;

[0048] Figure 7 is a schematic diagram of radial velocity fitting in an embodiment of the present invention;

[0049] Figure 8 is a schematic diagram of radial velocity interpolation processing in an embodiment of the present invention;

[0050] Figure 9 It is a schematic diagram of the geographic coordinate system;

[0051] Figure 10 It is a schematic diagram of the radar coordinate system. DETAILED DESCRIPTION

[0052] The present invention will be further described and illustrated below in conjunction with the accompanying drawings and specific embodiments. The technical solutions in the embodiments of this application are clearly and completely described. Obviously, the embodiments described 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 making creative work are within the scope of protection of the present invention.

[0053] A method for inverting wind profiles in a target area of ​​a ground-based laser radar comprises:

[0054] Step 1: Calculate the pitch and azimuth ranges that the radar beam needs to scan based on the coordinate relationship between the radar and the target position in the geographic coordinate system;

[0055] Step 1.1, as Figure 2 As shown in the figure, based on the geographic coordinate system, the coordinates of radar 1 are O(Lg1, La1, H1), the coordinates of target location 2 are P(Lg2, La2, H2), and the target area is detection airspace 3, where Lgi is longitude, Lai is latitude, and Hi is altitude (where i = 1, 2). The detection area of ​​airspace 3 is approximately a cylinder S, with the coordinates of the center axis of cylinder S on the ground being (Lg2, La2, H2), the radius of the cylinder being R, and the altitude resolution being h0.

[0056] Step 1.2: Divide the target area into corresponding grid points according to the target area wind profile detection altitude resolution. The grid points are divided into cubes. The cube area centered at the target position altitude is included in the altitude layer. Taking any detection altitude h as an example, the detection area at altitude layer h is a cylindrical sub-area with a height of h0 on the cylinder S, recorded as S h , S h The altitude of the lower surface is S h The altitude of the upper base is

[0057] Step 1.3, for cylinder S h For example, the cylindrical section at height h is denoted as g, the line connecting the center of radar 1 and g is denoted as m, and the theory of spatial solid geometry is used to solve the diameter l0 in plane g that is parallel to the normal vector of line m.

[0058] Divide the diameter l0 into four equal parts, take the five equal points of l0, and calculate the coordinates of the five equal points in the geographic coordinate system O1(x1,y1,z1), O2(x2,y2,z2), O3(x3,y3,z3), O4(x4,y4,z4), O5(x5,y5,z5), respectively. Connect point O with O1, O2, O3, O4, O5, then the vector (where i = 1, 2, ..., 5). The laser beams are respectively along the vector (where i = 1, 2, ..., 5) directions.

[0059] Step 1.4, through coordinate transformation, the coordinates of the laser beam are transformed from the geographic coordinate system to the radar coordinate system. The scanning azimuth and elevation angles in the radar coordinate system are θ i and γ i (i=1,2,…,5).

[0060] During measurement, the radar coordinates, target position coordinates, target airspace detection altitude, altitude resolution and other parameter information are input into the host computer software. The host computer software automatically calculates the scanning azimuth and pitch angles of all altitude layers in the target area, and establishes a scanning information database for all altitude layers using the two-dimensional array Coef[n][Attitude]. Among them, n represents the altitude layer, and Attitude represents the azimuth and pitch angle information of the radar scanning beam. This array is written into the initialization file when the host computer software is running.

[0061] Step 2: The radar performs a three-dimensional volume scan of the target detection area according to the azimuth and elevation angle ranges calculated in step 1 to obtain radial wind speed data for each range unit of each laser beam.

[0062] Step 2.1: Before measuring, the radar should face north. Figure 3 As shown, the radar is controlled to perform a three-dimensional volume scan of the target detection area according to the scanning azimuth and pitch information calculated in step 1. The scanning is performed layer by layer, and the process is repeated until all measurements are completed.

[0063] Step 2.2: According to the scanning parameters calculated in step 1, ensure that there is scanning data at any height layer in the target area, obtain the echo time domain data of each laser beam, and divide it into different distance units according to the distance size. The length of the distance unit is m0, where m0 should not be greater than like Figure 4 shown.

[0064] The radar digital receiver converts the radar signal from the intermediate frequency to the fundamental frequency through Hilbert transform, and performs spectrum transformation on the signal through the joint time-frequency analysis method based on variational mode decomposition. Multiple pulse echoes are non-coherently accumulated to obtain the original power spectrum data, which is stored in the two-dimensional array R[n][gate_num], where n represents the beam number and gate_num represents the range unit number.

[0065] In step 2.3, the power spectrum data R[n][gate_num] of each distance unit can be modeled as a random process that obeys the normal distribution. By calculating the statistical characteristics such as the expectation and variance of the random process, "expectation + weight coefficient × variance" is used as the adaptive threshold detection threshold. The data above the threshold is considered to be the signal envelope.

[0066] The signal envelope of each distance unit is detected, and the envelope centroid is obtained using the first-order moment to solve the signal peak position and intensity, and further calculate the Doppler frequency and radial wind speed data V ri ;

[0067] Step 3: Generate wind profile data of the target area based on the data obtained from the scanning detection and output

[0068] Step 3.1, Figure 5 The figure shows a cross-sectional view of the target area grid points. Taking into account the calculation accuracy and calculation scale, the number of grids is the total number N of height layers detected in the target area, and the height of the grid does not exceed the height resolution h0 of the target area.

[0069] For a specific altitude layer, the radial wind speed data of each distance unit obtained by radar scanning detection are divided into two categories. One category is the points falling within the range of the above-mentioned network grid points, that is, the coordinates of the distance unit where the radial wind is located in the geographic coordinate system fall into the grid point area of ​​the altitude layer, which is recorded as C rI The other type is the data where the coordinates of the distance unit of radial wind in the geographic coordinate system do not fall within the range of the above network grid points, which is recorded as C rO , where r = 1, 2, ..., N, represents the rth altitude layer of the target area. Figure 6 Shown is a stereogram of the target area grid points.

[0070] The comprehensive considerations in this step refer to both computational accuracy and scale. The scale is primarily related to the number of radial light velocity scans in step 2, which translates to the number of equations in steps 3.4. Because this is not the focus of this application, and those skilled in the art can optimize the relevant calculations based on existing techniques, this application does not discuss this technical aspect in detail.

[0071] Step 3.2, for each detection altitude layer in the target area, C rI There must be no less than three distance unit data within the range; if this requirement is not met, then C rO The radial wind speed data in each distance unit of the same laser beam are fitted with a recursive function curve, and the fitted curve is recorded as f, as shown in Figure 7 shown.

[0072] Step 3.3, interpolate the data to the required grid points according to the fitting function f in the above steps, and the interpolated C rI becomes C' rI ,like Figure 8 As shown, solid dots represent data that fall within the grid, hollow dots represent data that do not fall within the grid, and triangles represent interpolated data;

[0073] Step 3.4, combine the coordinate information of each beam and calculate the wind vector data set C' that falls into the same altitude layer. rI , we solve the following set of equations to obtain the three-dimensional wind vector (u, v, w) at that altitude. The conjugate gradient method and constrained multivariable linear optimization problem are used to find the optimal solution, which can avoid drastic changes in the fitting results caused by small changes in the acquisition parameters.

[0074]

[0075] Among them, V i,h (i=1,2,…,n) represents the i-th wind speed data falling into the altitude layer h, θ i Indicates wind speed data V i,h The corresponding azimuth angle in the radar's own coordinate system, β i Indicates wind speed data V i,h The corresponding elevation angle in the radar's own coordinate system.

[0076] Change the altitude parameters and repeat steps 3.1 to 3.4 until all altitude layers are calculated and the wind profile data for each altitude layer in the area are output.

[0077] The functions of the several steps of this application can be summarized as follows:

[0078] Step 1: coordinate definition and basic coordinate transformation;

[0079] Step 2 is how to use the echo signal to invert the radial velocity;

[0080] Step 3 is how to use the inverted radial velocity to invert the wind profile of the target area.

[0081] Those skilled in the art should understand that, in the disclosure of the present invention, the quantitative relationships indicated by "four equal divisions" and "five" are based on the positional relationships shown in the accompanying drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the algorithm must have a specific number of operations. Therefore, the above terms should not be understood as limiting the present invention.

[0082] The present invention is not limited to the above-described embodiments. The above-described embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims.

[0083] The present invention is not limited to the above-described embodiments. The above-described embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims.

Claims

1. A method for inverting wind profiles in a target area using a ground-based laser radar, characterized in that: include: Step 1: Calculate the elevation and azimuth ranges that the radar beam needs to scan based on the coordinate relationship between the radar and the target in the geographic coordinate system. Step 2: The radar performs a three-dimensional volume scan of the target detection area according to the azimuth and elevation angle ranges calculated in step 1, and obtains radial wind speed data for each range unit of each laser beam; Step 3: Invert the data obtained from the scanning detection to form the wind profile data of the target area and output it; The step 1 includes Step 1.1, based on the geographic coordinate system, the coordinates of the radar 1 position are O(Lg1, La1, H1), the coordinates of the detection target position 2 are P(Lg2, La2, H2), and the target area is the detection airspace 3, where Lgi is the longitude, Lai is the latitude, and Hi is the altitude. Where i = 1, 2, the detection area of ​​airspace 3 is approximately a cylinder S, the coordinates of the central axis of the cylinder S on the ground are (Lg2, La2, H2), the radius of the cylinder is R, and the height resolution is h0. Step 1.2: Divide the target area into corresponding grid points according to the target area wind profile detection altitude resolution. The grid points are divided into cubes. The cube areas centered at the target position altitude are all included in the altitude layer. Taking any detection altitude h as an example, the detection area at the altitude layer h is a cylindrical sub-area with a height of h0 on the cylinder S, recorded as S h , S h The altitude of the lower surface is S h The altitude of the upper base is Step 1.3, for cylinder S h For example, the cylindrical section at height h is denoted as g, and the line connecting the center of radar 1 and g is denoted as m. The theory of spatial solid geometry is used to solve the diameter l0 in plane g that is parallel to the normal vector of line m. Divide the diameter l0 into four equal parts, take five equal points of l0, and calculate the coordinates O1(x 1, y 1, z1), O2(x 2, y 2, z2), O3(x 3, y 3, z3), O4(x 4, y 4, z4), O5(x 5, y 5, z5), connect point O with O1, O2, O3, O4, O5 respectively, then the vector Where j = 1, 2, ..., 5 laser beams are respectively along the vector Among them, the direction of j=1,2,…,5 is scanned. Step 1.4, through coordinate transformation, the coordinates of the laser beam are transformed from the geographic coordinate system to the radar coordinate system. The scanning azimuth and elevation angles in the radar coordinate system are θ j and γ j , j=1,2,…,5, During measurement, the radar coordinates, target position coordinates, target airspace detection altitude, and altitude resolution parameter information are input into the host computer software. The host computer software automatically calculates the scanning azimuth and pitch angles of all altitude layers in the target area, and establishes a scanning information database for all altitude layers using a two-dimensional array Coef[n][Attitude]. Among them, n represents the altitude layer, and Attitude represents the azimuth and pitch angle information of the radar scanning beam. This array is written into the initialization file when the host computer software is running. The step 2 includes Step 2.1: Before measuring, the radar should face north first. The radar should be controlled to perform a three-dimensional volume scan of the target detection area according to the scanning azimuth and pitch information calculated in step 1. The scanning is performed layer by layer and the process is repeated until all measurements are completed. Step 2.2, obtain the echo time domain data of each laser beam, divide the echo time domain data into different distance units according to the distance size, and the length of the distance unit is m0, where m0 should not be greater than The digital receiver converts the radar signal from the intermediate frequency to the base frequency through Hilbert transform, and performs spectrum transformation on the signal through the joint time-frequency analysis method based on variational mode decomposition. Multiple pulse echoes are non-coherently accumulated to obtain the original power spectrum data, which is stored in the two-dimensional array R[n][gate_num], where n represents the beam number and gate_num represents the range unit number. Step 2.3: Smooth and denoise the power spectrum data R[n][gate_num] of each distance unit. Then, model the echo signal as a random process. By calculating the expectation and variance statistical characteristics of the random process, "expectation + weight coefficient × variance" is used as the adaptive threshold detection threshold. The data above the threshold is considered to be the signal envelope. The signal envelope of each distance unit is detected, and the envelope centroid is obtained using the first-order moment. The signal peak position and intensity are solved, and the Doppler frequency and radial wind speed data V are further calculated. rj ; The step 3 includes Step 3.1: Considering the calculation accuracy and calculation scale, the number of grids is the total number of height layers N detected in the target area, and the height of the grid does not exceed the height resolution h0 of the target area. For a specific altitude layer, the radial wind speed data of each distance unit obtained by radar scanning detection are divided into two categories. One category is the points falling within the range of the above-mentioned network grid points, that is, the coordinates of the distance unit where the radial wind is located in the geographic coordinate system fall into the grid point area of ​​the altitude layer, which is recorded as C rI The other type is the data where the coordinates of the distance unit of radial wind in the geographic coordinate system do not fall within the range of the above network grid points, which is recorded as C rO , where r = 1, 2, ..., N, represents the rth altitude layer of the target area, Step 3.2, for each detection altitude layer in the target area, C rI There must be no less than three distance unit data within the range; if this requirement is not met, then C rO The radial wind speed data in each distance unit of the same laser beam are fitted with a recursive function curve, and the fitted curve is recorded as f. Step 3.3, interpolate the data to the required grid points according to the fitting function f in the above steps, and the interpolated C rI becomes C' rI , solid dots represent data that fall within the grid, hollow dots represent data that do not fall within the grid, and triangles represent interpolated data. Step 3.4, combine the coordinate information of each beam and calculate the wind vector data set C' that falls into the same altitude layer. rI , according to the following equations, the three-dimensional wind vector (u, v, w) at this altitude layer is obtained. The equations are solved by using the conjugate gradient method and the constrained multivariable linear optimization problem to find the optimal solution, avoiding the drastic change of the fitting results caused by the slight change of the acquisition parameters. Among them, V k,h , k=1,2,…,n represents the kth wind speed data falling into the altitude layer h, ψ k Indicates wind speed data V k,h The corresponding azimuth in the radar coordinate system, β k Indicates wind speed data V k,h The corresponding elevation angle in the radar's own coordinate system.

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