Boat-borne meteorological radar three-dimensional wind field inversion method based on multi-angle asymmetric coplanar analysis

Abstract

The invention belongs to the technical field of meteorological radars, and particularly relates to an airship-borne meteorological radar three-dimensional wind field inversion method based on multi-angle asymmetric coplanar analysis, and the method specifically comprises the steps: enabling an airship to fly linearly in a certain direction, and carrying out the volume scanning, doppler radial velocity and radar scanning information of a target observed at each parking position of the airship-borne meteorological radar are acquired, and the position and slant distance of the target are calculated; dividing every two parking position observation results into one group, and selecting a combination meeting performance optimization conditions based on the performance optimization conditions of the MA-ASCAT model; on the basis of an inversion formula of an MA-ASCAT model, first two dimensions under a cylindrical coordinate system are obtained through inversion by utilizing the screened combination, and a third dimension is solved according to the wind speeds of the first two dimensions on the basis of an incompressible mass continuity equation; and converting the three-dimensional wind speed under the cylindrical coordinate system into a Cartesian coordinate system, so that the three-dimensional wind field inversion method is completed.

Description

Technical Field

[0001] The present invention belongs to the technical field of meteorological radars, and particularly relates to a method for retrieving three-dimensional wind fields of shipborne meteorological radars based on multi-angle asymmetric coplanar analysis. Background Art

[0002] Disaster weather such as typhoons has a long development cycle and extremely high destructive power. Retrieving three-dimensional wind fields is crucial for understanding the kinematics and dynamics inside disaster weather such as typhoons and predicting their evolution and tracking. High-altitude airships have the advantage of long-term information observation of key areas compared with space-based platforms. Compared with ground-based platforms, they have the advantages of long line-of-sight distance and flexible deployment, and are very suitable for complete observation of weather systems with long development cycles. Therefore, weather radars should possess the technical ability to retrieve three-dimensional wind fields under airship platforms.

[0003] Currently, there are mainly three observation means and methods for disaster weather: the method for retrieving three-dimensional wind fields based on conditional assumptions applied to ground-based weather radars, the fixed-angle coplanar analysis technology applied to airborne meteorological radars, and the observation of wind fields based on spaceborne lidar. Ground-based weather radars have poor long-distance detection capabilities, only observe specific areas, and the typhoon wind field is complex, and the linear wind field assumption fails, making it impossible to achieve refined inversion. The fixed-angle coplanar analysis technology applied to airborne meteorological radars requires the rapid movement of the platform to obtain radial velocity observations of the same target from different perspectives. Due to the slow flight speed of airships, this algorithm cannot achieve continuous coverage of the wind field under airship platforms. Under space-based systems, spaceborne lidar can only observe the vertical profile of the global wind field, and there is currently no effective observation means for observing the three-dimensional wind field of the global atmosphere.

[0004] Therefore, the above traditional algorithms are not applicable to the retrieval of three-dimensional wind fields based on airship platforms. Summary of the Invention

[0005] A method for retrieving three-dimensional wind fields of shipborne meteorological radars based on multi-angle asymmetric coplanar analysis provided by the present invention aims to solve problems such as the slow speed of airships, the complex and rapidly changing wind fields of disaster weather such as typhoons, and realizes refined three-dimensional wind field observation of long-term developing weather systems such as typhoons on airship platforms.

[0006] The technical solution to achieve the present invention is as follows:

[0007] A method for retrieving three-dimensional wind fields of shipborne meteorological radars based on multi-angle asymmetric coplanar analysis, the specific process is as follows:

[0008] Step 1, the airship flies straight along a certain direction and performs volume scanning to obtain the Doppler radial velocity of the target observed at each stop position of the shipborne meteorological radar and the radar scanning information, and calculate the position and slant range of the target;

[0009] Step 2: Divide the observation results of every two parking positions into a group, and select the combination that meets the performance optimization conditions based on the performance optimization conditions of the multi-angle asymmetric coplanar analysis technique (MA-ASCAT) model;

[0010] Step 3: Inversion of the first two-dimensional wind field: Based on the inversion formula of the MA-ASCAT model, use the combination selected in Step 2 to invert the first two dimensions in the cylindrical coordinate system, that is, the radial wind speed U in the cylindrical coordinate system ρ and the wind speed U in the central axis direction in the cylindrical coordinate system Y , and the central axis direction is the straight flight direction of the airship;

[0011] Step 4: Inversion of the third-dimensional wind field: Based on the incompressible mass continuity equation, solve the third dimension according to the wind speeds of the first two dimensions, that is, the wind speed U in the direction perpendicular to the radial direction and increasing along the angle in the cylindrical coordinate system a ;

[0012] Step 5: Convert the three-dimensional wind speed in the cylindrical coordinate system to the Cartesian coordinate system, and thus complete a three-dimensional wind field inversion method for an airship-mounted meteorological radar based on multi-angle asymmetric coplanar analysis.

[0013] Optionally, in the present invention, it is assumed that the airship has N parking positions, and volume scanning is adopted at each parking position of the airship. For each target, there will be N(N - 1) / 2 combination methods, and each combination method means that each target is observed by the airship-mounted meteorological radar at two different parking positions;

[0014] Establish a (ρ, a, Y) cylindrical coordinate system with the Y-axis of the airship flight direction as the central axis, obtain the Doppler radial velocity and radar scan information of each combination method, and calculate the position and slant range of each target.

[0015] Optionally, the optimization conditions in the MA-ASCAT model in Step 2 of the present invention include formula (10) and formula (11):

[0016]

[0017] where τ en is the downward viewing angle, R n is the distance between the radar and the target, σ rn is the error variance of the radial observation velocity V rn , ρ represents the distance from the target to the Y-axis, n = 1, 2 represents the two observation numbers of each combination method;

[0018]

[0019] where β nis the separation angle, Y n is the mooring position of the airship, and Y is the position of the target;

[0020] When the observation results of the two mooring positions simultaneously satisfy formula (10) and formula (11), it is determined that this combination meets the performance optimization conditions.

[0021] Optionally, for the combination that meets the performance optimization conditions screened in step 2 of the present invention, a scanning strategy is further designed, specifically: according to the combination method obtained by screening in advance according to the performance optimization conditions and the observation information under this combination method, the number of scanning layers during radar scanning is designed in advance to improve the scanning efficiency.

[0022] Optionally, the scanning in the present invention is a pitch scan at a fixed azimuth angle or a horizontal rotation scan at a fixed pitch angle.

[0023] Optionally, the inversion formula in step 3 of the present invention is:

[0024]

[0025] where V rn represents the radar radial observation velocity, Y n is the mooring position of the airship, R n is the distance between the radar and the target, ρ represents the distance from the target to the Y-axis, and Y is the position of the target.

[0026] Optionally, for the integral solution of the third-dimensional wind field component U a in step 4 of the present invention, the specific process is:

[0027] First, based on the incompressible mass continuity equation, integrate and solve for U a as:

[0028]

[0029] where a m-1 and a m are the previous and subsequent integral positions of the integral path;

[0030] Secondly, calculate f(a) according to the inversion formula of the first two-dimensional wind speed as:

[0031]

[0032] Finally, initialize the zenith plane and the ground plane respectively. In the cylindrical coordinate system, for each ρ-a plane, find the equal-ρ curve and integrate and solve for U a along the a direction.

[0033] Optionally, converting the three-dimensional wind speed in the cylindrical coordinate system to the Cartesian coordinate system in step 5 of the present invention is:

[0034] u = U ρ sinα + U a cosα

[0035] v = U Y

[0036] w = -U ρ cosα + U a sinα

[0037] Wherein, α represents the azimuth of the target relative to the central axis (i.e., the Y-axis) in the cylindrical coordinate system.

[0038] Beneficial effects:

[0039] For the problem of three-dimensional wind field inversion of shipborne meteorological radar, the MA-ASCAT method observes the Doppler velocity of the same pixel point from multiple different perspectives, designs a reasonable scanning strategy according to performance advantages and disadvantages, decouples the first two-dimensional wind field components according to geometric relationships, and applies a strong constraint through the incompressible mass continuity equation, thereby integrating and solving the third wind field component. Compared with the traditional algorithm FA-SACT, this method not only further improves the performance of wind field inversion, but also can achieve continuous coverage of the wind field, which helps HAPS to conduct more complete observations on disaster weather systems with long development cycles such as typhoons. The inversion of its three-dimensional wind field is helpful for studying the mechanism of mesoscale and small-scale weather systems and improving the accuracy of nowcasting. Therefore, based on the multi-angle asymmetric coplanar analysis technology of shipborne meteorological radar, this application can achieve large-range and high-precision three-dimensional wind field inversion of disaster weather such as typhoons. Brief description of the drawings

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0041] Figure 1 It is the scanning geometry diagram of the MA-ASCAT algorithm of the present invention;

[0042] Figure 2 It is the area that can be covered in the volume scanning mode of Embodiment 1 of the present invention;

[0043] Figure 3 It is the retrievable area after screening the performance optimization conditions in Embodiment 1 of the present invention;

[0044] Figure 4 It is the RMSE histogram of the three-dimensional wind field inversion of Embodiment 1 of the present invention and the traditional algorithm in the cylindrical coordinate system;

[0045] Figure 5 This is the inversion performance diagram of the three-dimensional wind field of the first embodiment of the present invention and the traditional algorithm in the Cartesian coordinate system. Specific implementation manners

[0046] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0047] It should be noted that, without conflict, the following embodiments and the features in the embodiments may be combined with each other; and, based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present disclosure.

[0048] It should be noted that the following describes various aspects of the embodiments within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is for illustrative purposes only. Based on the present disclosure, those skilled in the art should understand that one aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of the aspects described herein may be used to implement the device and / or practice the method. Additionally, this device and / or method may be implemented using other structures and / or functionality in addition to one or more of the aspects described herein.

[0049] The embodiment of the present application provides a three-dimensional wind field inversion method for a boat-mounted meteorological radar based on multi-angle asymmetric coplanar analysis, including:

[0050] Step 1, the airship flies straight along a certain direction and performs volume scanning to obtain the Doppler radial velocity of the target observed at each stop position of the boat-mounted meteorological radar and the radar scanning information, and calculate the position and slant range of the target;

[0051] Step 2, divide the observation results of every two stop positions into a group, and select the combination that meets the performance optimization conditions based on the performance optimization conditions of the multi-angle asymmetric coplanar analysis technology (MA-ASCAT) model;

[0052] Step 3, inversion of the first two-dimensional wind field: Based on the inversion formula of the MA-ASCAT model, use the combination selected in Step 2 to invert the first two-dimensional wind speeds in the cylindrical coordinate system, that is, the radial wind speed U in the cylindrical coordinate system ρ and the wind speed U in the central axis direction in the cylindrical coordinate system Y , and the central axis direction is the straight flight direction of the airship;

[0053] Step 4, third-dimension wind field inversion: Based on the incompressible mass continuity equation, solve for the third-dimension wind speed according to the wind speeds in the first two dimensions, that is, the wind speed U perpendicular to the radial direction and along the direction of increasing angle in the cylindrical coordinate system. a ;

[0054] Step 5, convert the three-dimensional wind speed in the cylindrical coordinate system to the Cartesian coordinate system, thus completing a three-dimensional wind field inversion method for an airship-mounted meteorological radar based on multi-angle asymmetric coplanar analysis.

[0055] Furthermore, when specifically implementing Step 1 of this embodiment, it specifically is:

[0056] The airship moves linearly in a certain direction and performs volume scanning. For the same target, at least two observed radial velocities V r1 and V r2 can be obtained. Establish a (ρ, a, Y) cylindrical coordinate system with the Y-axis in the airship flight direction as the central axis, where the variable ρ is the distance from the target to the Y-axis, and a is the coplanar angle starting from 0° in the zenith plane (x = 0 plane) and increasing to the right of the Y-axis; at the same time, a g -x g y g z g rectangular coordinate system is defined, and the origins of the two coordinate systems are the same, both being a point in the flight direction. P is the target point, R n (n = 1 or 2) is the distance between the radar and the target point P in the previous and subsequent scans, Y n is the position of the airship in the two perspectives, τ n is the pitch angle, and τ en is the lower perspective, is the separation angle (the angle between R n and ρ), and for the specific illustration, please refer to Figure 1 .

[0057] During the process of the airship moving along the Y-axis, it is assumed that there are N (N≥2) stop positions, and the airship performs volume scanning at each stop point. For each observation point, there will be combinations. Each combination means that each observation point is observed by the airship-mounted radar at two different stop positions, that is, there are observed radial velocities at two different perspectives. Obtain the Doppler radial velocity and radar scan information of the target observed at each stop position of the airship-mounted meteorological radar, and calculate the position and slant range of the target.

[0058] Further, in step 2 of this embodiment, every two observation results of the stopping positions are grouped, and based on the performance optimization conditions of the multi-angle asymmetric coplanar analysis technology (MA-ASCAT) model, a combination that meets the performance optimization conditions is selected. Among them, the multi-angle asymmetric coplanar analysis technology (MA-ASCAT) model of the embodiment of the present application includes a three-dimensional wind field inversion model and performance optimization conditions. The derivation process of the MA-ASCAT model will be described in detail below:

[0059] Assume that the three-dimensional wind speed at the observation point in the cylindrical coordinate system is U ρ 、U a and U Y , then the observed radial velocity V rn from different perspectives can be expressed as:

[0060] V r1 = U ρ cosβ1 + U Y sinβ1 (1)

[0061] V r2 = U ρ cosβ2 + U Y sinβ2 (2)

[0062] The inversion model of the first two-dimensional wind field can be obtained by decoupling:

[0063]

[0064] The derivation process of the performance optimization conditions (i.e., formula (10) and formula (11)) is as follows:

[0065] For the fixed elevation angle symmetric coplanar analysis technology (FA-SCAT) of the traditional algorithm, the algorithm is limited to the symmetry of the two perspectives with respect to the target P, which can be regarded as a special case of the proposed algorithm (i.e., R1 = R2, r1 = r2, Y1 - Y = Y - Y2, where Y is the coordinate of the target P). According to the error transfer principle and the inversion formulas (3) and (4), the error variances σ ρ and U Y of U 2 ρs and σ 2 Ys ;

[0066] For FA-SCAT, there is:

[0067]

[0068] where σ rn is the error variance of the radial observation velocity V rn , and n = 1, 2.

[0069] Similarly, for MA-ASCAT, there is σ 2 ρd and σ 2 Yd :

[0070]

[0071]

[0072] First, analyze σ ρ 2 to construct a cost function Let It is easy to know that k1 + k2 = 1; where The cost function J can be derived as follows:

[0073]

[0074] Regarding J ≤ 0 as a unary quadratic inequality according to formula (9) and assuming Solve for k2 to get:

[0075]

[0076] where τ en is the lower viewing angle,

[0077] Similarly, for the error variance of U Y MA-ASCAT improves σ 2 Y compared to FA-SCAT, and the performance optimization condition is:

[0078]

[0079] Compared with FA-SCAT, MA-ASCAT does not have to be limited to the same lower viewing angle for the two consecutive observations. According to the performance optimization conditions derived from the MA-ASCAT model constructed in step 1, as shown in formula (10) and formula (11), this combination method can be screened for performance.

[0080] Based on the above performance optimization conditions, the specific screening process is as follows:

[0081] For airships at N different parking positions, when performing RHI (RHI scan is to make a pitch scan at a fixed azimuth angle or PPI (PPI scan is to rotate horizontally at a fixed pitch angle) scan, each target will be scanned N times, and every two scans form a combination, so there will be a total of Combination methods. Determine which combination methods have position and observation information such as the lower viewing angle, azimuth angle, scanning radius, and separation angle, etc. (i.e., the position of the airship and the position of the target relative to the airship), which meet the performance optimization formulas (10) and (11). The formulas that meet the performance optimization conditions record the combined position and observation information, and those that do not meet are discarded. According to the recorded position and observation information above, the number of scanning layers required for the airship to perform RHI scanning or PPI scanning at each parking position can be counted.

[0082] At the same time, select the observation points that meet the performance optimization conditions and reasonably design the scanning strategy. Specifically: Based on the combination methods obtained by screening according to the performance optimization conditions in advance and the observation information under this combination method, design the number of scanning layers during radar scanning in advance to improve the scanning efficiency.

[0083] Furthermore, based on the inversion models of the first two-dimensional wind fields in step 3, namely formulas (3) and (4), and at the same time based on the scanning strategy in step 2, select appropriate combinations of radial observation velocities for the first two-dimensional wind field components U ρ and U Y in the cylindrical coordinate system for inversion.

[0084] Furthermore, in the derivation process of the MA - ASCAT model given above, the derivation of the third-dimensional wind field model is still lacking. This process gives the calculation process of the third-dimensional wind field model:

[0085] Solve for the third-dimensional wind field component according to the incompressible mass continuity equation. Under the assumption that the air density remains unchanged, the incompressible mass continuity equation is:

[0086]

[0087] According to formula (12), integrate to solve for U a It can be obtained that:

[0088]

[0089] Among them, a m-1 and a m are the previous and subsequent integration positions of the integration path. Combining the inversion formulas (3) and (4), there is:

[0090]

[0091] Based on this, U a needs to be initialized before the integration starts, that is, find a reliable integration starting point (boundary condition). In the cylindrical coordinate system, the integration starting points are mainly divided into two categories: ① a = 0 zenith plane (plane x = 0) ② z = 0 ground plane.

[0092] For ① a = 0 zenith plane

[0093] Select small angles ±Δa on both sides of the zenith plane. Assuming that the vertical velocity w is constant and the horizontal velocity u (in the x - direction) is linear within this range, we can obtain:

[0094]

[0095] For the ground surface plane of ②z = 0

[0096] Adopt the anti - seepage condition as the boundary condition, that is, at the ground surface plane z = 0, the vertical velocity w = 0. From this, we can obtain:

[0097]

[0098] Assume that the coplanar angles along the integration path are arranged in sequence as a0, a1, a2,..., a n , where a0 is the coplanar angle at the starting position of the integration path, and a n is the coplanar angle at the ending position of the integration path. Then the expression of U i at the position with the coplanar angle a a is:

[0099]

[0100] Optionally, the step 5 includes:

[0101] Through steps 1 - 4, the three - dimensional wind field in the cylindrical coordinate system can be obtained. From the following conversion relation formula (18), the three - dimensional wind field (U ρ , U a , U Y ) in the cylindrical coordinate system can be converted to the Cartesian coordinate system (u, v, w)

[0102] u = U ρ sin a+U a cos a

[0103] v = U Y (18)

[0104] w = - U ρ cos a+U a sin a

[0105] where a represents the azimuth of the target relative to the central axis (i.e., the Y - axis) in the cylindrical coordinate system. In this scenario, a cylindrical coordinate system is established with the airship flight direction axis as the central axis. Among them, the variable ρ is the distance from the target to the Y - axis, and a is the coplanar angle starting from 0° in the zenith plane (x = 0 plane) and increasing to the right of the Y - axis.

[0106] Thus, the three - dimensional wind field inversion method of the on - board meteorological radar based on multi - angle asymmetric coplanar analysis is completed.

[0107] Example:

[0108] In this embodiment, the scenario sets the airship to fly straight at an altitude of 20 km and simultaneously adopts volume scanning at the parking positions separated by 25 km. The specific scenario scale parameters and airship motion parameters are shown in Table 1.

[0109] The WRF numerical simulation data is used as the three-dimensional wind field "true value", and the "true value" is projected onto the radial direction. On this basis, a Gaussian distribution Doppler error with a mean of 0 and a variance of 1 is introduced to obtain the radial observation velocity under the perspective of each parking position.

[0110] In addition, the scanning speed is related to the cumulative number of pulses. If the cumulative number of pulses is too large, the scanning time will increase. Otherwise, the standard deviation of the Doppler velocity estimation will deteriorate. Therefore, we need to balance the relationship between the scanning time and the standard deviation of the Doppler velocity estimation. A spectral width of 4 m / s can cover most weather conditions. When the spectral width is 4 m / s and the number of pulse accumulations is 18, the standard deviation of the Doppler velocity estimation can be controlled at about 1 m / s.

[0111] Table 1

[0112]

[0113]

[0114] This embodiment provides a specific method for inverting the three-dimensional wind field by an airship-borne meteorological radar. The specific steps are as follows:

[0115] Step 1, specifically including:

[0116] Construct the MA-ASCAT model, select the middle parking position as the origin, and record the Doppler radial velocity information V of each target observed at each parking position (0, Y m , 0) (Y m = -25, 0, 25. Here, the subscript m represents the parking position), the down viewing angle τ rm during radar scanning, the slant range R em and the azimuth angle θ m . Record the position information (ρ, a, Y) of each target and the horizontal projection r n of the slant range R m through the above information: m :

[0117] r m = R m sinτ em (19)

[0118]

[0119] Step 2 specifically includes:

[0120] During the actual detection process, due to the limitation of the antenna rotation speed, the selection range of the elevation angle should not be too large. If the selection range of the elevation angle is too small, the detection range with better performance will also become smaller accordingly. These two requirements need to be considered in a balanced way. Therefore, in this example, the range of the elevation angle is limited to 25° to 65°. At the same time, select the position information of the pixel points and the radar parking position information that meet the performance optimization conditions of Formula (10) and Formula (11). The area that can be covered in the volume scan mode is shown in Figure 2 , the colormap color mapping shows the number of times the pixel points can be observed when the parking position N = 3. The area that can be retrieved after being screened by the performance optimization conditions is shown in Figure 3 .

[0121] Step 3 specifically includes:

[0122] Retrieve the wind field components in the first two dimensions:

[0123] Substitute the position information (ρ, a, Y) of the pixel points recorded in Step 1, that is, the radial velocities V rn (n = 1, 2, where the subscript n here refers to the two perspectives before and after), into Formula (3) and Formula (4), and then the wind field components U ρ , U Y can be solved.

[0124] Step 4 specifically includes:

[0125] Integrate to solve the wind field component U in the third dimension a : First, initialize the zenith plane and the ground plane respectively. In the cylindrical coordinate system, for each ρ - a plane, find the isometric ρ curve, and integrate U along the a direction a to solve. The traditional algorithm FA - SCAT can only retrieve the central area between two parking positions and requires the same lower viewing angles before and after. The RMSE histogram of the inversion of MA - ASCAT and FA - SCAT in the cylindrical coordinate system is shown in Figure 4 .

[0126] Step 5 specifically includes:

[0127] Convert the three - dimensional wind field in the cylindrical coordinate system obtained by inversion to the Cartesian coordinate system according to Formula (18). The inversion performance of this technology compared with the traditional technology in the Cartesian coordinate system is shown in Figure 5, the three lines from top to bottom are the u, v, and w three-dimensional wind field components: (a)-(c) are the true values of the three-dimensional wind field at a certain height; (d)-(f) are the inversion results of the three-dimensional wind field by the traditional algorithm FA-SCAT at a certain height; (g)-(i) are the inversion results of the three-dimensional wind field by the algorithm MA-ASCAT of the present invention at a certain height; (k)-(l) are the differences between the inversion results of the three-dimensional wind field by the algorithm MA-ASCAT of the present invention at a certain height and the true values. Thus, the three-dimensional wind field inversion method of the shipborne meteorological radar based on multi-angle asymmetric coplanar analysis is completed.

[0128] From Figure 4 and Figure 5 it can be seen that in the case of U ρ , U Y , the inversion error can be controlled within 1 m / s. In the case of U a , the error is relatively large, mainly due to certain errors brought about by the assumption of boundary conditions during initialization, and at the same time, the error accumulates due to integral solution. And u, w are closely related to U a . Generally speaking, compared with the traditional technology, this technology not only expands the inversion area to achieve continuous coverage of the wind field, but also improves the inversion performance. Therefore, it can be considered that the three-dimensional wind field inversion can be realized under the shipborne platform by the algorithm of the present invention. This algorithm is not only limited to shipborne radars, but also applicable to the collaborative observation of multiple ground-based radars.

[0129] The above content is a further detailed description of the present invention in combination with specific implementation manners, and it cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention pertains, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should all be regarded as belonging to the protection scope of the present invention.

[0130] In summary, the above is only a preferred embodiment of the present invention and is not used to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for inverting three-dimensional wind field of a shipborne meteorological radar based on multi-angle asymmetric coplanar analysis, characterized in that: The specific process is: Step 1: The airship flies in a straight line in a certain direction and performs volume scanning to obtain the Doppler radial velocity and radar scanning information of the target observed by the onboard weather radar at each stop position, and calculate the position and slant range of the target; Step 2, grouping every two parking position observation results into one group, and selecting a combination that meets the performance optimization condition based on the performance optimization condition of the multi-angle asymmetric coplanar analysis technology MA-ASCAT model; Step 3, inversion of the first two dimensions of wind field: Based on the inversion formula of the MA-ASCAT model, using the combination selected in step 2, the first two dimensions in the cylindrical coordinate system are inverted, namely the radial wind speed U ρ and the wind speed in the central axis direction U Y ; Step 4, third dimension wind field inversion: Based on the incompressible mass continuity equation, the third dimension U is solved according to the wind speed of the first two dimensions a ; Step 5, convert the three-dimensional wind speed in the cylindrical coordinate system to the Cartesian coordinate system, thus realizing the three-dimensional wind field inversion.

2. The method for three-dimensional wind field inversion of a shipborne meteorological radar based on multi-angle asymmetric coplanar analysis according to claim 1 is characterized in that: Assume that the airship has N parking positions, and the airship uses volume scanning at each parking position. For each target, there will be N(N-1) / 2 combinations, and each combination means that each target is observed by the airship weather radar at two different parking positions. The (ρ, a, Y) cylindrical coordinate system is established with the Y axis of the airship flight direction as the central axis to obtain the Doppler radial velocity and radar scanning information of each combination, and calculate the position and slant range of each target.

3. The method for three-dimensional wind field inversion of a shipborne meteorological radar based on multi-angle asymmetric coplanar analysis according to claim 1 is characterized in that: The optimization conditions in the MA-ASCAT model in step 2 include formula (10) and formula (11): Among them, τ en For the lower perspective, R n is the distance between the radar and the target, σ rn is the radial observation velocity V rn The error variance is ρ, which represents the distance from the target to the Y axis. n=1,2 represents the two observation numbers for each combination; β n is the separation angle, Y n is the airship parking position, Y is the target position; When the two parking position observation results satisfy formula (10) and formula (11) at the same time, it is determined that the combination meets the performance optimization condition.

4. The method for three-dimensional wind field inversion of a shipborne meteorological radar based on multi-angle asymmetric coplanar analysis according to claim 1 is characterized in that: In step 2, the combination that meets the performance optimization conditions is screened out, and a scanning strategy is further designed, specifically: the number of scanning layers during radar scanning is designed in advance according to the combination method obtained by screening the performance optimization conditions and the observation information under the combination method, so as to improve the scanning efficiency.

5. The method for three-dimensional wind field inversion of a shipborne meteorological radar based on multi-angle asymmetric coplanar analysis according to claim 1 is characterized in that: The scanning is pitch scanning at a fixed azimuth angle or rotating scanning in the horizontal direction at a fixed pitch angle.

6. The method for three-dimensional wind field inversion of a shipborne meteorological radar based on multi-angle asymmetric coplanar analysis according to claim 3 is characterized in that: The inversion formula in step 3 is: Among them, V rn represents the radar radial observation velocity, Y n is the airship parking position, R n is the distance between the radar and the target, ρ represents the distance from the target to the Y axis, and Y is the position of the target.

7. The method for three-dimensional wind field inversion of a shipborne meteorological radar based on multi-angle asymmetric coplanar analysis according to claim 6 is characterized in that: Step 4 integrates and solves the third-dimensional wind field component U a , the specific process is: First, based on the incompressible mass continuity equation, we can solve U a for: Among them, a m-1 and a m are the previous integral position and the next integral position of the integral path; Secondly, according to the wind speed inversion formula of the first two dimensions, f(a) is calculated as: Finally, initialize the zenith plane and the surface plane respectively. In the cylindrical coordinate system, for each ρ-a plane, find the equal ρ curve and calculate the U a Solve the integral.

8. The method for three-dimensional wind field inversion of a shipborne meteorological radar based on multi-angle asymmetric coplanar analysis according to claim 1 is characterized in that: The step 5 converts the three-dimensional wind speed in the cylindrical coordinate system to the Cartesian coordinate system as follows: u=U ρ sina+U a what v=U Y w=-U ρ thing+U a sina Where a represents the orientation of the target relative to the central axis in the cylindrical coordinate system.

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