Raindrop spectrum inversion method and device based on optimal estimation model, medium and product

Abstract

The invention provides a raindrop spectrum inversion method and device based on an optimal estimation model, a medium and a product, and the method comprises the steps: carrying out the inversion of a raindrop spectrum through employing a raindrop inversion-based optimal estimation model according to observation values obtained by a ka-waveband radar, a W-waveband radar and a C-waveband radar at a preset height, and obtaining an inversion result at the preset height, according to the invention, under the condition that inversion results of other layers are not influenced, the effect of inversion of raindrop spectrum absolute number concentrations and aerodynamic parameters at all heights can be realized, and the problem of mutual influence of errors among all layers is solved.

Description

Technical Field

[0001] The present application relates to raindrop spectrum inversion technology, and in particular to a raindrop spectrum inversion method, equipment, medium and product based on an optimal estimation model. Background Art

[0002] Raindrop spectrum inversion refers to the process of deriving the size distribution of raindrops from observation data obtained by radar or other remote sensing means. This technology is widely used in weather forecasting, climate research, and hydrological analysis.

[0003] Existing raindrop spectrum inversion methods are all based on dual-band radar inversion, which cannot accurately obtain the absolute concentration of the raindrop spectrum; multi-step inversion is required, and it is impossible to invert the raindrop spectrum at all heights. The inversion results obtained are prone to mutual influence between different layers.

[0004] In view of the above defects, the present application provides a raindrop spectrum inversion method, equipment, medium and product based on an optimal estimation model. Summary of the invention

[0005] The present application provides a raindrop spectrum inversion method, equipment, medium and product based on an optimal estimation model, which can achieve the effect of inverting the absolute number concentration and aerodynamic parameters of the raindrop spectrum at each height, and solve the problem of mutual influence of errors between layers.

[0006] In a first aspect, an embodiment of the present application provides a raindrop spectrum inversion method based on an optimal estimation model, comprising:

[0007] Obtain observation data of Ka-band radar, W-band radar and C-band radar at a preset altitude;

[0008] Obtaining a preliminary guess of a raindrop spectrum parameter according to the observation data; the raindrop spectrum parameter includes a raindrop spectrum, an attenuation value of the Ka-band radar, an attenuation value of the W-band radar, and vertical air movement;

[0009] Establishing an optimal estimation model based on raindrop inversion, the optimal estimation model based on raindrop inversion includes a forward model based on raindrop inversion and a state variable, the input of the forward model based on raindrop inversion is an initial guess value of the state variable, and the output of the forward model based on raindrop inversion is a calculated value of the Ka-band radar power spectrum and a calculated value of the W-band radar power spectrum;

[0010] The initial guess values ​​of the raindrop spectrum parameters and the preset air broadening spectrum width are used as the initial guess values ​​of the state variables, the power spectrum observed by the Ka-band radar and the W-band radar and the reflectivity factor of the C-band after absolute calibration are used as the observation values ​​of the optimal estimation model based on raindrop inversion and input into the optimal estimation model based on raindrop inversion, and the inversion result of the raindrops at the preset height output by the optimal estimation model based on raindrop inversion is obtained, and the inversion result includes the output value of the state variable.

[0011] In one possible design, the forward model based on raindrop inversion includes:

[0012] S ka (V,r)=A ka (r) [S R，ka (VW air , r)*S A，ka (V, r)]+S f,ka

[0013] S W (V,r)=A W (r)[S R,W (VW air ,r)*S A,W (V,r)]+S f,w

[0014]

[0015] Wherein, V is the Doppler velocity, r represents the preset height of the raindrop, S ka (V, r) and S W (V, r) represent the power spectra actually observed by Ka-band radar and W-band radar, respectively. S R,ka and S R,W are the backscattering powers actually generated by rainfall particles observed by Ka-band radar and W-band radar, respectively. ka (r) and A W (r) represents the total attenuation of Ka-band radar and W-band radar, respectively, S A,ka and S A,W represent the air broadening kernel of Ka-band radar and W-band radar respectively, W air Indicates the vertical movement of air, S f,ka and S f,W Respectively represent the background noise of Ka-band radar and W-band radar; σ b,ka (D), σ b,W (D) and σ b,c (D) represents the scattering cross section related to raindrop diameter under Ka-band radar, W-band radar and C-band radar, respectively. N represents the number of raindrops, D represents the raindrop diameter, and σair represents the width of the air broadened spectrum, c is the propagation speed of electromagnetic waves, C c represents the C-band radar calibration constant, K is the dielectric constant of water; Z c represents the reflectivity factor measured by C-band radar, A rain,c It represents the attenuation of C-band radar due to raindrops. Since the attenuation of C-band radar is very small, this value can be ignored in actual inversion. * represents the convolution operator.

[0016] In a possible design, the observation data includes observation values ​​of the power spectrum of the Ka-band radar, the power spectrum of the W-band radar, and the power spectrum of the C-band radar; and obtaining an initial guess value of a raindrop spectrum parameter according to the observation data includes:

[0017] Obtaining an initial guess value of the raindrop spectrum at the preset height by using a radar power spectrum inversion method according to the power spectrum of the Ka-band radar;

[0018] Obtaining a preliminary guess of the attenuation value of the ka radar and a preliminary guess of the attenuation value of the W band radar according to the observed value of the reflectivity factor of the C band radar;

[0019] The initial guess value of the vertical air motion is obtained by inverting the power spectrum of the Ka-band radar and the power spectrum of the W-band radar through a table lookup method.

[0020] In a possible design, obtaining the initial guess value of the attenuation value of the ka radar and the initial guess value of the attenuation value of the W-band radar according to the observed value of the reflectivity factor of the C-band radar includes:

[0021] Obtaining the absolute calibrated reflectivity factor according to the observation value of the C-band radar;

[0022] According to the reflectivity factor of the absolute calibration, the initial guess value of the attenuation value of the ka radar and the initial guess value of the attenuation value of the W-band radar are respectively obtained by the following formulas:

[0023] k rain_Ka =0.01Z lin 0.63

[0024] k rain_w =0.14Z lin 0.44

[0025] Among them, Z lin is the linear representation of the absolute calibrated reflectivity factor, k rain_ka and k rain_W They represent the attenuation of Ka-band radar and W-band radar due to raindrops respectively.

[0026] In a possible design, obtaining an initial guess value of the vertical motion by inverting the power spectrum of the Ka-band radar and the power spectrum of the W-band radar through a table lookup method includes:

[0027] According to the theoretical Doppler spectrum ratio formula of Ka and W bands in the absence of air broadening, a lookup table of Doppler spectrum ratios corresponding to differential attenuation within a first preset range and air vertical motion within a second preset range is established; the lookup table is matched with the observed value of the Doppler spectrum ratio, and the obtained value of the air vertical motion is used as an initial guess of the air vertical motion.

[0028] In a possible design, the method of obtaining an initial guess of the raindrop spectrum at the preset height by using a radar power spectrum inversion method according to the power spectrum of the Ka-band radar includes:

[0029] Obtaining a pre-inverted first raindrop spectrum using a radar power spectrum formula according to the power spectrum of the Ka-band radar;

[0030] Performing gamma fitting on the first raindrop spectrum to obtain a second raindrop spectrum;

[0031] The second raindrop spectrum is sampled to obtain an initial guess value of the raindrop spectrum.

[0032] In a second aspect, an embodiment of the present application provides a raindrop spectrum inversion device based on an optimal estimation model, comprising:

[0033] A receiving module is used to obtain observation data of Ka-band radar, W-band radar and C-band radar at a preset altitude;

[0034] An acquisition module, used to acquire an initial guess value of a raindrop spectrum parameter according to the observation data; the raindrop spectrum parameter includes a raindrop spectrum, an attenuation value of the Ka-band radar, an attenuation value of the W-band radar, and vertical air movement;

[0035] A model module, used to establish an optimal estimation model based on raindrop inversion, wherein the optimal estimation model based on raindrop inversion includes a forward model based on raindrop inversion and a state variable, the input of the forward model based on raindrop inversion is an initial guess value of the state variable, and the output of the forward model based on raindrop inversion is a calculated value of the Ka-band radar power spectrum and a calculated value of the W-band radar power spectrum;

[0036] An inversion module is used to take the initial guess value of the raindrop spectrum parameter and the preset air broadening spectrum width as the initial guess value of the state variable, and take the power spectrum observed by the Ka-band radar and the W-band radar and the reflectivity factor of the C-band after absolute calibration as the observation values ​​of the optimal estimation model based on raindrop inversion, and input them into the optimal estimation model based on raindrop inversion, so as to obtain the inversion result of the raindrops at the preset height output by the optimal estimation model based on raindrop inversion, wherein the inversion result includes the output value of the state variable.

[0037] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor;

[0038] The memory stores computer-executable instructions;

[0039] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0040] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0041] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0042] The embodiments of the present application provide a raindrop spectrum inversion method, device, medium and product based on the optimal estimation model. The method includes: according to the observation values ​​obtained by the three band radars of Ka-band, W-band radar and C-band at a preset height, the raindrop spectrum is inverted by using the raindrop inversion optimal estimation model to obtain the inversion result at the preset height, and the inversion of the single-layer height of the raindrop spectrum is realized without affecting the inversion results of other layers, which can well solve the problem of mutual influence of errors between layers. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0044] Figure 1 A schematic diagram of a raindrop spectrum inversion method based on an optimal estimation model provided in an embodiment of the present application Figure 1 ;

[0045] Figure 2A schematic diagram of a raindrop spectrum inversion method based on an optimal estimation model provided in an embodiment of the present application Figure 2 ;

[0046] Figure 3 A schematic diagram of a process of step S220 provided in an embodiment of the present application;

[0047] Figure 4 A flowchart of step S230 provided in an embodiment of the present application;

[0048] Figure 5 A schematic diagram of a raindrop spectrum inversion method based on an optimal estimation model provided in an embodiment of the present application Figure 3 ;

[0049] Figure 6 A convergence result diagram of the ka band in the single-layer inversion result provided in the embodiment of the present application;

[0050] Figure 7 A graph showing the convergence results of the W band in the single-layer inversion results provided in the embodiment of the present application;

[0051] Figure 8 A DSD result diagram of a single-layer inversion result provided in an embodiment of the present application;

[0052] Fig. 9 A convergence result diagram of the ka band in the multi-layer inversion results provided in the embodiment of the present application;

[0053] Fig.10 A graph showing the convergence results of the W band in the multi-layer inversion results provided in the embodiment of the present application;

[0054] Fig.11 A result diagram of raindrop velocity at different heights in the multi-layer inversion result provided in an embodiment of the present application;

[0055] Fig.12 DSD result diagrams at different heights in the multi-layer inversion results provided in the embodiments of the present application;

[0056] Fig.13 A schematic diagram of the structure of a raindrop spectrum inversion device based on an optimal estimation model provided in an embodiment of the present application;

[0057] Fig.14 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0058] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0059] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims, rather than all embodiments. Based on the embodiments in 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.

[0060] In the specification and claims of the present application and the above-mentioned drawings, the terms "first", "second", and "third" are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the objects used in this way can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example.

[0061] It should be noted that the “at…” in the embodiments of the present application may be the instant when a certain situation occurs, or may be a period of time after the occurrence of a certain situation, and the embodiments of the present application do not specifically limit this.

[0062] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0063] Figure 1 A schematic diagram of a raindrop spectrum inversion method based on an optimal estimation model provided in an embodiment of the present application Figure 1 .like Figure 1 As shown, the method includes:

[0064] S101, obtaining observation data of Ka-band radar, W-band radar and C-band radar at a preset altitude;

[0065] Specifically, Ka-band, W-band and C-band are frequency ranges commonly used in radar technology. The frequency of Ka-band is 2.56GHz~40GHz, and the wavelength is about 7.5mm~11mm. The frequency of W-band is 75GHz~110GHz, and the wavelength is about 2.7mm~4mm. The frequency of C-band is 5.6GHz, and the wavelength is about 5.4cm.

[0066] S102, obtaining an initial guess of a raindrop spectrum parameter according to the observed data; the raindrop spectrum parameter includes the number of particles under a preset particle size, the attenuation value of the Ka-band radar, the attenuation value of the W-band radar, and the vertical movement of air;

[0067] Specifically, the raindrop spectrum parameters include observation data including the power spectrum of the Ka-band radar, the power spectrum of the W-band radar, and the observed values ​​of the reflectivity factor of the C-band radar;

[0068] Specifically, the initial guess values ​​of the raindrop spectrum parameters can be obtained through existing inversion methods based on the observation data.

[0069] S103, establishing an optimal estimation model based on raindrop inversion, wherein the optimal estimation model based on raindrop inversion includes a forward model based on raindrop inversion and a state variable, wherein the input of the forward model based on raindrop inversion is an initial guess value of the state variable, and the output of the forward model based on raindrop inversion is a calculated value of a Ka-band radar power spectrum and a calculated value of a W-band radar power spectrum;

[0070] Specifically, the Optimal Estimation Model (OE) is a widely used data assimilation and inversion technology. Its purpose is to estimate the state variables by maximizing the posterior probability distribution based on the observed data and guessed values ​​of the state variables, by minimizing a certain cost function (based on the observation error covariance matrix and the state variable covariance matrix), combining the observed data and prior knowledge, based on Bayesian statistical theory, to improve the accuracy and reliability of parameter estimation and find the most likely state variables.

[0071] S104. Taking the initial guess values ​​of the raindrop spectrum parameters and the preset air broadening spectrum width as the initial guess values ​​of the state variables, taking the power spectrum observed by the Ka-band radar and the W-band radar and the reflectivity factor of the C-band after absolute calibration as the observation values ​​of the optimal estimation model based on raindrop inversion, input them into the optimal estimation model based on raindrop inversion, and obtaining the inversion result of the raindrops at the preset height output by the optimal estimation model based on raindrop inversion, wherein the inversion result includes the output value of the state variable.

[0072] Specifically, the raindrop spectrum parameters and air broadening spectrum width output by the optimal estimation model based on raindrop inversion are the raindrop spectrum inversion results at the preset height, which can reduce the mutual influence of errors between layers.

[0073] Figure 2 A schematic diagram of a raindrop spectrum inversion method based on an optimal estimation model provided in an embodiment of the present application Figure 2 ;like Figure 2 As shown, the method includes:

[0074] S210, obtaining observation data of Ka-band radar, W-band radar and C-band radar at a preset altitude; the observation data includes observation values ​​of the power spectrum of the Ka-band radar, the power spectrum of the W-band radar and the reflectivity factor of the C-band radar;

[0075] Specifically, the data are corrected for height according to the actual vertical resolution of the three-band radars, and the data matching the detection height is obtained based on the Ka-band range resolution (30m), and the time resolution is based on the 2-second observation time of Ka and W;

[0076] Specifically, the preset altitude is the altitude layer where the maximum signal-to-noise ratio of the W-band radar power spectrum is greater than 10 dB, and the number of spectrum points with a signal-to-noise ratio greater than 5 dB is not less than 90;

[0077] Specifically, since the W-band has the largest attenuation and is most likely to produce a situation where the signal-to-noise ratio does not meet the conditions, the W-band radar power spectrum data is used to screen the preset height.

[0078] S220, obtaining an initial guess value of a raindrop spectrum by using a radar power spectrum inversion method according to a power spectrum of a Ka-band radar;

[0079] As an example, Figure 3 , S220 can be achieved through the following steps:

[0080] S221, obtaining a pre-inverted first raindrop spectrum by using a radar power spectrum formula according to the power spectrum of the Ka-band radar;

[0081] Specifically, the radar power spectrum formula is:

[0082] S v (V,r)=A v (r)[S R，v (VW air , r)*S A,v (V,r)]+S f (1)

[0083]

[0084] Among them, S ν (V, r) is the power spectrum actually observed by the radar at a frequency of v; V is the falling speed of the raindrops; D is the particle size of the raindrops, S R，v (V, r) is the backscattering power actually generated by rainfall particles; S f is the background noise; W air Indicates the vertical movement of air, S A,v represents the air broadening core, K is the dielectric constant of water, N is the number of raindrops; σ b (D) represents the particle size-dependent scattering cross section. ρ is the air density at a preset height, ρ0 is the air density at 100HPa.

[0085] We assume that the air broadening is very small, so there is no need to perform the deconvolution step when inverting the initial guess of the raindrop spectrum. The power spectrum observed by the Ka-band radar is substituted into the above formula, and the first raindrop spectrum of the pre-inversion is calculated by the inverse operation of the above formula.

[0086] S222, performing gamma fitting on the first raindrop spectrum to obtain a second raindrop spectrum;

[0087] Specifically, the gamma fitting model is a common raindrop spectrum fitting data, which is established on the basis of assuming that the raindrops conform to the gamma probability distribution function. This step is used to reduce the number of particles at the small particle end of the first raindrop spectrum.

[0088] S223: Sampling the second raindrop spectrum to obtain an initial guess value of the raindrop spectrum.

[0089] Specifically, the second raindrop spectrum may be sampled at a preset sampling period to obtain an initial guess value of the raindrop spectrum.

[0090] As an implementation method, the particle size range of the second raindrop spectrum is 0-8 mm, and the sampling period is 0.1 mm. Then, the number of the initial guess values ​​of the obtained raindrop spectrum is 80.

[0091] S230, obtaining an initial guess value of the attenuation value of the ka radar and an initial guess value of the attenuation value of the W band radar according to the observed value of the reflectivity factor of the C band radar;

[0092] Specifically, Figure 4 , this step includes:

[0093] S231, obtaining an absolutely calibrated reflectivity factor Z according to observation data of the C-band radar;

[0094] Specifically, the reflectivity factor is a physical quantity that describes the intensity of the echo received by the radar, usually expressed in decibels (dBZ).

[0095] Specifically, obtaining an absolutely calibrated reflectivity factor is a key step in ensuring the accuracy and reliability of radar data, and can be obtained by using methods such as the standard target method and the reference radar method in the prior art.

[0096] S232 obtains the initial guess values ​​of the attenuation value of the ka radar and the attenuation value of the W band radar respectively according to the absolute calibration reflectivity factor Z by the following formulas:

[0097] k rain_Ka =0.01Z lin 0.63 (4)

[0098] k rain_w =0.14Z lin 0.44 (5)

[0099] Specifically, the attenuation of Ka and W band radars has a strong correlation with the reflectivity factor of C band radar, which can be obtained using the above formula. rain_ka and k rain_W They represent the attenuation of Ka-band radar and W-band radar due to raindrops; Z lin It is the linear representation of the reflectivity factor of Z absolute calibration. The specific conversion formula is:

[0100] Z=10log 10 (Z lin ) (6)

[0101] S240, obtaining an initial guess of the vertical motion of the air by inverting the power spectrum of the Ka-band radar and the power spectrum of the W-band radar through a table lookup method.

[0102] Specifically, according to the theoretical Doppler spectrum ratio formula of the Ka and W bands in the absence of air broadening, a lookup table of Doppler spectrum ratios corresponding to differential attenuation within a first preset range and air vertical motion within a second preset range is established; the lookup table is matched with the observed value of the Doppler spectrum ratio, and the obtained value of the air vertical motion is used as an initial guess of the air vertical motion.

[0103] Specifically, in the absence of air broadening, the theoretical Doppler spectrum ratio formula for the Ka and W bands is:

[0104]

[0105] Where DSR is the Doppler spectrum ratio, S ka and S W They represent the power spectra observed by Ka-band radar and W-band radar, respectively, and represent the ratio of the power spectrum data of Ka-band radar and W-band radar, λ ka and λ W denote the wavelengths of Ka-band radar and W-band radar respectively, σ b,ka (D), σ b,W (D) and σ b,c (D) represents the scattering cross section related to the raindrop diameter under Ka-band radar, W-band radar and C-band radar respectively; N represents the number of raindrops.

[0106] Specifically, when the width of the air broadening spectrum in the actual atmosphere is determined, the vertical movement of the air will not change the shape of the DSR, but will only cause the DSR to move left and right along the horizontal axis. The magnitude of the differential attenuation between the Ka and W bands will not affect the shape of the DSR, but will only cause the DSR to move up and down along the vertical axis. In other words, the specific value of the DSR is only affected by the differential attenuation and the vertical movement of the air.

[0107] Specifically, in the absence of air spectrum broadening and air vertical motion, the first peak position of the theoretical DSR (differential attenuation and air vertical motion are both 0) of the Ka and W bands corresponds to the first Mie scattering point of the W band, i.e., 5.9 m / s. For radars with two wavelengths determined, its DSR can be simplified to the above formula (7) to obtain the theoretical DSR. It can be seen that it is not affected by the raindrop spectrum distribution.

[0108] Specifically, according to formulas (1) and (2), by assigning different values ​​of air vertical motion, the power spectrum calculation values ​​of the Ka-band radar and the power spectrum calculation values ​​of the W-band radar can be obtained respectively (the N in the formula can be used to randomly fit a set of raindrop spectrum concentrations using the gamma function, which does not affect the results). The logarithmic Doppler spectrum ratio 10log10 (DSR) of the Ka-band radar and the W-band radar can be obtained by comparing the power spectrum calculation values ​​of the Ka-band radar and the power spectrum calculation values ​​of the W-band radar. On this basis, different differential attenuation values ​​ΔA can be directly added or subtracted. ka，W , get the simulated DSRsim, there are as many DSRsim as there are combinations of air vertical motion and differential attenuation lookup tables.

[0109] As an embodiment, the differential attenuation in the lookup table takes -20dB to 20dB, with an interval of 2dB, for a total of 40 values; the vertical movement of air takes -4m / s to 4m / s, with an interval of 0.1m / s, for a total of 80 values; 3200 combinations of differential attenuation and vertical movement of air can be obtained, and 3200 corresponding DSRsim can be obtained.

[0110] Similarly, the DSR of the observed value can be calculated based on the power spectrum observation value of the Ka-band radar and the power spectrum observation value of the W-band radar. obs , find and DSR obs The closest DSR sim At this time, the corresponding vertical air movement and differential attenuation are confirmed as the vertical air movement W air And the initial guess of the differential attenuation ΔA.

[0111] Furthermore, the embodiment of the present application also includes: a method for correcting an initial guess value of the attenuation value of the W-band radar according to an initial guess value of the differential attenuation, the method comprising:

[0112] A first differential attenuation value is obtained according to the difference between an initial guess of the attenuation value of the Ka-band radar and an initial guess of the attenuation value of the W-band radar. If the error between the first differential attenuation value and the initial guess of the differential attenuation is not within a preset error range, the difference between the initial guess of the attenuation value of the Ka-band radar and the initial guess of the differential attenuation is obtained as an initial guess of the attenuation value of the new W-band radar.

[0113] S250, establishing an optimal estimation model based on raindrop inversion, wherein the optimal estimation model based on raindrop inversion includes a forward model based on raindrop inversion and a state variable, wherein the input of the forward model based on raindrop inversion is an initial guess value of the state variable, and the output of the forward model based on raindrop inversion is a calculated value of a Ka-band radar power spectrum and a calculated value of a W-band radar power spectrum;

[0114] Specifically, the forward model based on raindrop inversion includes:

[0115] S ka (V,r)=A ka (r)[S R,ka (VW air ,r)*S A,ka (V,r)]+S f,a (8)

[0116] S W (V,r)=A W (r)[S R,W (VW air , r)*S A,W (V,r)]+S f,w (9)

[0117]

[0118] Where V is the Doppler velocity, r is the preset height of the raindrop, S ka (V, r) and S W (V, r) represent the power spectra actually observed by Ka-band radar and W-band radar, respectively. S R,ka and S R,W are the backscattering powers actually generated by rainfall particles observed by Ka-band radar and W-band radar, respectively. ka (r) and A W (r) represents the total attenuation of Ka-band radar and W-band radar, respectively, S A,ka and S A,W represent the air broadening kernel of Ka-band radar and W-band radar respectively, W air Indicates the vertical movement of air, S f,ka and S f,W Respectively represent the background noise of Ka-band radar and W-band radar; σ b,ka (D), σb,W (D) and σ b,c (D) represents the scattering cross section related to raindrop diameter under Ka-band radar, W-band radar and C-band radar, respectively. N represents the number of raindrops, D represents the raindrop diameter, and σ air represents the width of the air broadened spectrum, c is the propagation speed of electromagnetic waves, C c represents the C-band radar calibration constant, K is the dielectric constant of water; Z c represents the reflectivity factor measured by C-band radar, A rain,c It represents the attenuation of C-band radar due to raindrops. Since the attenuation of C-band radar is very small, this value can be ignored in actual inversion. * represents the convolution operator.

[0119] Specifically, the optimal estimation model based on raindrop inversion also includes a covariance matrix of state variables and a covariance matrix of observations.

[0120] Specifically, the covariance matrix of the state variables is used to characterize the statistical errors of the state variables. The optimal estimation model based on raindrop inversion adjusts the state variables through the matrix. The diagonal items of the covariance matrix of the state variables are used to characterize the errors of the raindrop spectrum, vertical air motion, air broadening spectrum width, and attenuation values ​​of ka and W-band radars. The positions corresponding to the raindrop spectrum are set to the values ​​of the initial guess of the raindrop spectrum itself, and the positions corresponding to the vertical air motion, air broadening spectrum width, and attenuation of ka and W-band radars are set to 0.5, 0.5, 3, and 3, respectively. In the non-diagonal items of the covariance matrix of the state variables, the part related to the raindrop spectrum is obtained by calculating the covariance of the data of the ground raindrop spectrometer for a period of time, and the rest is set to 0.

[0121] Specifically, the covariance matrix of the observed value is used to characterize the observation error of the observed value; the diagonal terms are set to 6 dB. For power spectra with a signal-to-noise ratio greater than 3 and the number of valid spectrum points greater than 330, the covariance matrix of the corresponding positions of 50 spectrum points near 6 m / s is set to 3 dB to focus on fitting the Mie scattering points in the W band. The non-diagonal terms are set to 0.

[0122] As an embodiment, the signal power corresponding to the 10% position in the horizontal coordinate of the power spectrum observed by the Ka-band radar and the W-band radar is taken as S f,ka and S f,W .

[0123] Furthermore, the model parameters also include other parameters such as the Jacobian ratio matrix, which can directly adopt the built-in parameters in the existing pyOptimalEstimation.py module.

[0124] S260, taking the initial guess values ​​of the raindrop spectrum parameters and the preset air broadening spectrum width as the initial guess values ​​of the state variables, taking the power spectrum observed by the Ka-band radar and the W-band radar and the reflectivity factor of the C-band after absolute calibration as the observation values ​​of the optimal estimation model based on raindrop inversion, and inputting them into the optimal estimation model based on raindrop inversion, and obtaining the inversion result of the raindrops at the preset height output by the optimal estimation model based on raindrop inversion, wherein the inversion result includes the output value of the state variable.

[0125] Furthermore, considering that the air broadening is small in most cases, the preset air broadening spectrum width is set to a relatively low level of 0.01 m / s.

[0126] Specifically, according to the above implementation, the number of initial guess values ​​of the raindrop spectrum obtained is 80 values, including the attenuation value of the Ka-band radar, the attenuation value of the W-band radar, the vertical movement of the air, and the preset air broadening spectrum width; the initial guess values ​​of its state variables total 84 values;

[0127] Specifically, due to the different velocity resolutions of the Ka-band and W-band radars, the Ka-band data is interpolated to the corresponding velocity points based on the W-band with higher velocity resolution, so that the Doppler power spectra of Ka and W have the same velocity resolution, and each radar spectrum still has 512 spectral points. The reflectivity factor Z of the C-band that has been absolutely calibrated is selected, and the observation value matrix is ​​composed of 1025 values.

[0128] Furthermore, in the iterative process of the optimal estimation model based on raindrop inversion, the calculated value of the power spectrum directly calculated according to the forward model iteration has only 80 spectral points. In order to facilitate comparison with the observed value, the 80 spectral points need to be interpolated to have the same velocity resolution as the power spectrum of the observed value, and 512 spectral points are obtained. The spectral points corresponding to the two bands are 1024 in total, plus the reflectivity factor Z obtained according to formula (15) C , the output value is 1025 in total.

[0129] Specifically, according to the preset number of iterations of the optimal estimation model based on raindrop inversion, the value of the state variable obtained is the output value of the optimal estimation model based on raindrop inversion, that is, the inversion result of this method. The inversion result includes the inversion value of the raindrop spectrum, the inversion value of the Ka-band radar attenuation value, the inversion value of the W-band radar attenuation and the inversion value of the vertical motion of the air;

[0130] Furthermore, according to the above inversion results, combined with the spectrum drawing tool, the raindrop spectrum at the preset inversion height and the convergence results of the Ka band and the W band can be further obtained;

[0131] Furthermore, by using the method provided in the embodiment of the present application, it is possible to obtain inversion results at different preset heights and to obtain inversion results of raindrop contours.

[0132] Through the method provided in the embodiment of the present application, we analyzed the precipitation in a county in Anhui Province on July 11, 2024. The height layer interval was 30m every two seconds. The method provided in the embodiment of the present application was used to perform an inversion and obtain the raindrop spectrum inversion results at multiple heights. Figure 5 Can reflect its process.

[0133] like Figure 6 to Figure 8 is the result of single-layer inversion at a certain height, such as Figures 9 to 12 These are the multi-layer inversion results obtained after inverting each altitude layer.

[0134] Figure 6 A convergence result diagram of the ka band in the single-layer inversion result provided in the embodiment of the present application; Figure 7 A graph showing the convergence results of the W band in the single-layer inversion results provided in the embodiment of the present application; Figure 8 This is a DSD result diagram of a single-layer inversion result provided in an embodiment of the present application; wherein ini is the result of the first forward model output, Obs is the radar observation value, and reslut is the result diagram.

[0135] Fig. 9 A convergence result diagram of the ka band in the multi-layer inversion results provided in the embodiment of the present application; Fig.10 A graph showing the convergence results of the W band in the multi-layer inversion results provided in the embodiment of the present application; Fig.11 A result diagram of raindrop velocity at different heights in the multi-layer inversion result provided in an embodiment of the present application; Fig.12 This is a DSD result diagram at different heights in the multi-layer inversion results provided in the embodiment of the present application. Fig. 9 and Fig.10 The orange color is the guessed value, and the blue color is the inversion result value.

[0136] according to Figure 6 to Figure 8 It can be seen that after 5-6 iterations, the inversion can successfully converge, and the converged power spectrum is in good agreement with the observed power spectrum. The inverted raindrop size distribution (DSD) can well reflect the changes in the number concentration of each particle size segment. Figures 9 to 12 , which can reflect the advantages of single-layer inversion. There are inversion anomalies near 700 meters in the lower layer, but it does not affect the inversion of other layers. It can well solve the problem of mutual influence of errors between layers.

[0137] The embodiment of the present application provides a raindrop spectrum inversion method based on an optimal estimation model, including: establishing an optimal estimation model based on raindrop inversion, the optimal estimation model based on raindrop inversion includes a forward model based on raindrop inversion and state variables, the input of the forward model based on raindrop inversion is the initial guess value of the state variable, and the output of the forward model based on raindrop inversion is the calculated value of the ka-band radar power spectrum and the calculated value of the W-band radar power spectrum; using the initial guess value of the raindrop spectrum parameter and the preset air broadening spectrum width as the initial guess value of the state variable, and inputting the power spectrum observed by the ka-band radar and the W-band radar and the reflectivity factor of the C-band after absolute calibration as the observation value of the optimal estimation model based on raindrop inversion into the optimal estimation model based on raindrop inversion, and obtaining the inversion result of raindrops at a preset height output by the optimal estimation model based on raindrop inversion, and the inversion result includes the output value of the state variable. It has the following beneficial effects:

[0138] Traditional inversion results are mostly based on the assumption that raindrops conform to probability distributions such as Gamma distribution and Log-normal distribution. The actual raindrop distribution has a large error with each probability distribution. The optimal estimation model based on raindrop inversion in the method provided in the embodiment of the present application is established on the basis of the power spectrum calculation formula, the backscatter power calculation formula, the radar attenuation value calculation formula and the radar reflectivity factor calculation formula (Formulas (8) to (13)). It can break away from the assumptions of the above probability distributions and obtain the real absolute concentration of raindrop spectrum distribution and air motion parameters. The inversion results of raindrop spectrum and air motion parameters obtained are more real and reliable.

[0139] The embodiment of the present application can reflect subtle changes in precipitation based on three-band high temporal and high spatial resolution observations, providing a reliable basis for us to understand the microphysical process of precipitation formation; the initial guess values ​​of the state variables obtained by the method of this embodiment provide reliable initial values ​​for the optimal estimation model based on raindrop inversion, thereby improving the accuracy of the raindrop spectrum inversion results.

[0140] With respect to the two-step inversion method in the prior art, the embodiment of the present application can perform one-step inversion through the optimal estimation model, thereby greatly improving the inversion efficiency.

[0141] The embodiment of the present application can invert the raindrop spectrum based on the observation values ​​obtained by the three band radars of Ka-band, W-band radar and C-band at a preset height, and obtain the inversion result at the preset height by using the raindrop inversion optimal estimation model. Without affecting the inversion results of other layers, the inversion of a single layer height of the raindrop spectrum is realized, which can well solve the problem of mutual influence of errors between layers.

[0142] According to the inversion results at multiple preset heights obtained by the method adopted in this application, since the layers will not affect each other, the inversion error between different heights is reduced, and the changes in the raindrop spectrum in the vertical direction can be obtained more accurately, which can help us understand the collision and breakup of raindrops during the falling process.

[0143] Fig.13 The present application provides a raindrop spectrum inversion device based on an optimal estimation model. Fig.13 , the inversion device 1300 comprises:

[0144] The receiving module 1310 is used to obtain the observation data of the Ka-band radar, the W-band radar and the C-band radar at a preset altitude;

[0145] The acquisition module 1320 is used to obtain the initial guess value of the raindrop spectrum parameter according to the observation data; the raindrop spectrum parameter includes the raindrop spectrum, the attenuation value of the Ka-band radar, the attenuation value of the W-band radar and the vertical movement of the air;

[0146] A model module 1330 is used to establish an optimal estimation model based on raindrop inversion, wherein the optimal estimation model based on raindrop inversion includes a forward model based on raindrop inversion and a state variable, wherein the input of the forward model based on raindrop inversion is an initial guess value of the state variable, and the output of the forward model based on raindrop inversion is a calculated value of a Ka-band radar power spectrum and a calculated value of a W-band radar power spectrum;

[0147] The inversion module 1340 is used to use the initial guess values ​​of the raindrop spectrum parameters and the preset air broadening spectrum width as the initial guess values ​​of the state variables, and use the power spectrum observed by the Ka-band radar and the W-band radar and the reflectivity factor of the C-band after absolute calibration as the observation values ​​of the optimal estimation model based on raindrop inversion, and input them into the optimal estimation model based on raindrop inversion, so as to obtain the inversion result of the raindrops at the preset height output by the optimal estimation model based on raindrop inversion, and the inversion result includes the output value of the state variable.

[0148] Specifically, the forward model based on raindrop inversion includes:

[0149] S ka (V,r)=A ka (r)[S R,ka (VW air ,r)*S A,ka (V,r)]+S f,ka

[0150] S W (V,r)=A W (r)[S R，w (VW air ,r)*S A,W (V,r)]+Sf，W

[0151]

[0152] Where V is the Doppler velocity, r is the preset height of the raindrop, S ka (V, r) and S W (V, r) represent the power spectra actually observed by Ka-band radar and W-band radar, respectively. S R,ka and S R,W are the backscattering powers actually generated by rainfall particles observed by Ka-band radar and W-band radar, respectively. ka (r) and A W (r) represents the total attenuation of Ka-band radar and W-band radar, respectively, S A,ka and S A,W represent the air broadening kernel of Ka-band radar and W-band radar respectively, W air Indicates the vertical movement of air, S f,ka and S f,W Respectively represent the background noise of Ka-band radar and W-band radar; σ b,ka (D), σ b,W (D) and σ b,c (D) represents the scattering cross section related to raindrop diameter under Ka-band radar, W-band radar and C-band radar, respectively. N represents the number of raindrops, D represents the raindrop diameter, and σ air represents the width of the air broadening spectrum, c is the propagation speed of electromagnetic waves, represents the calibration constant of the C-band radar, K is the dielectric constant of water; represents the reflectivity factor measured by the C-band radar, A rain,c It represents the attenuation of C-band radar due to raindrops. Since the attenuation of C-band radar is very small, this value can be ignored in actual inversion. * represents the convolution operator.

[0153] Further, the observation data includes the power spectrum of the Ka-band radar, the power spectrum of the W-band radar, and the observation value of the reflectivity factor of the C-band radar; the acquisition module 1320 is also used to:

[0154] According to the power spectrum of the Ka-band radar, the initial guess of the raindrop spectrum at the preset height is obtained by using the radar power spectrum inversion method;

[0155] Obtaining a preliminary guess of the attenuation value of the ka radar and a preliminary guess of the attenuation value of the W band radar according to the observed value of the reflectivity factor of the C band radar;

[0156] According to the power spectrum of Ka-band radar and W-band radar, the initial guess of vertical air motion is obtained by table lookup method.

[0157] Furthermore, the acquisition module 1320 is further configured to:

[0158] Obtaining the absolute calibrated reflectivity factor based on the C-band radar observations;

[0159] According to the reflectivity factor of absolute calibration, the initial guess values ​​of the attenuation value of the Ka radar and the initial guess values ​​of the attenuation value of the W band radar are obtained by the following formulas:

[0160] k rain_Ka =0.01Z lin 0.63

[0161] k rain_W =0.14Z lin 0.44

[0162] Among them, Z lin is the linear representation of the absolute calibrated reflectivity factor, k rain_ka and k rain_W They represent the attenuation of Ka-band radar and W-band radar due to raindrops respectively.

[0163] Furthermore, the acquisition module 1320 is further configured to:

[0164] According to the theoretical Doppler spectrum ratio formula of Ka and W bands in the absence of air broadening, a lookup table of Doppler spectrum ratios corresponding to differential attenuation within a first preset range and air vertical motion within a second preset range is established; the lookup table is matched with the observed value of the Doppler spectrum ratio, and the obtained value of the air vertical motion is used as an initial guess of the air vertical motion.

[0165] Furthermore, the acquisition module 1320 is further configured to:

[0166] According to the power spectrum of the Ka-band radar, the first raindrop spectrum of the pre-inversion is obtained by using the radar power spectrum formula;

[0167] Perform gamma fitting on the first raindrop spectrum to obtain a second raindrop spectrum;

[0168] The second raindrop spectrum is sampled to obtain an initial guess of the raindrop spectrum.

[0169] The implementation principle and technical effect of the inversion device provided in this embodiment are similar to those of the above-mentioned inversion method, and are not described in detail in this embodiment.

[0170] Fig.14 This is a schematic diagram of the structure of an electronic device provided in this application. Fig.14 As shown, the electronic device 140 provided in this embodiment includes: at least one processor 1401 and a memory 1402. Optionally, the device 140 also includes a communication component 1403. The processor 1401, the memory 1402 and the communication component 1403 are connected via a bus 1404.

[0171] In a specific implementation process, at least one processor 1401 executes the computer-executable instructions stored in the memory 1402, so that at least one processor 1401 executes the above method.

[0172] The specific implementation process of the processor 1401 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0173] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0174] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0175] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0176] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0177] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0178] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0179] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0180] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0181] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0182] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0183] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0184] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0185] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0186] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A raindrop spectrum inversion method based on an optimal estimation model, characterized in that: include: Obtain observation data of Ka-band radar, W-band radar and C-band radar at a preset altitude; Obtaining a preliminary guess of a raindrop spectrum parameter according to the observation data; the raindrop spectrum parameter includes a raindrop spectrum, an attenuation value of the Ka-band radar, an attenuation value of the W-band radar, and vertical air movement; Establishing an optimal estimation model based on raindrop inversion, the optimal estimation model based on raindrop inversion includes a forward model based on raindrop inversion and a state variable, the input of the forward model based on raindrop inversion is an initial guess value of the state variable, and the output of the forward model based on raindrop inversion is a calculated value of the Ka-band radar power spectrum and a calculated value of the W-band radar power spectrum; The initial guess values ​​of the raindrop spectrum parameters and the preset air broadening spectrum width are used as the initial guess values ​​of the state variables, the power spectrum observed by the Ka-band radar and the W-band radar and the reflectivity factor of the C-band after absolute calibration are used as the observation values ​​of the optimal estimation model based on raindrop inversion and input into the optimal estimation model based on raindrop inversion, and the inversion result of the raindrops at the preset height output by the optimal estimation model based on raindrop inversion is obtained, and the inversion result includes the output value of the state variable.

2. The method according to claim 1, characterized in that: The forward model based on raindrop inversion includes: S ka (V,r)=A ka (r)[S R,ka (V-W air ,r)*S A,ka (V,r)]+S f,ka S W (V,r)=A W (r)[S R,W (V-W air ,r)*S A,W (V,r)]+S f,W Wherein, V is the Doppler velocity, r represents the preset height of the raindrop, S ka (V, r) and S W (V, r) represent the power spectra actually observed by Ka-band radar and W-band radar, respectively. S R,ka and S R,W are the backscattering powers actually generated by rainfall particles observed by Ka-band radar and W-band radar, respectively. ka (r) and A W (r) represents the total attenuation of Ka-band radar and W-band radar, respectively, S A,ka and S A,W represent the air broadening kernel of Ka-band radar and W-band radar respectively, W air Indicates the vertical movement of air, S f,ka and S f,W Respectively represent the background noise of Ka-band radar and W-band radar; σ b,ka (D), σ b,W (D) and σ b,c (D) represents the scattering cross section related to raindrop diameter under Ka-band radar, W-band radar and C-band radar, respectively. N represents the number of raindrops, D represents the raindrop diameter, and σ air represents the width of the air broadened spectrum, c is the propagation speed of electromagnetic waves, C C represents the C-band radar calibration constant, K is the dielectric constant of water; Z c represents the reflectivity factor measured by C-band radar, A rain,c It represents the attenuation of C-band radar due to raindrops. Since the attenuation of C-band radar is very small, this value can be ignored in actual inversion. * represents the convolution operator.

3. The method according to claim 1, characterized in that The observation data includes the power spectrum of the Ka-band radar, the power spectrum of the W-band radar, and the observation value of the reflectivity factor of the C-band radar; the initial guess value of the raindrop spectrum parameter is obtained according to the observation data; including: Obtaining an initial guess value of the raindrop spectrum at the preset height by using a radar power spectrum inversion method according to the power spectrum of the Ka-band radar; Obtaining an initial guess value of the attenuation value of the ka radar and an initial guess value of the attenuation value of the W band radar according to the observed value of the reflectivity factor of the C band radar; The initial guess value of the vertical air motion is obtained by inverting the power spectrum of the Ka-band radar and the power spectrum of the W-band radar through a table lookup method.

4. The method according to claim 3, characterized in that The step of obtaining the initial guess value of the attenuation value of the ka radar and the initial guess value of the attenuation value of the W band radar according to the observed value of the reflectivity factor of the C band radar comprises: Obtaining the absolute calibrated reflectivity factor according to the observation value of the C-band radar; According to the reflectivity factor of the absolute calibration, the initial guess value of the attenuation value of the Ka radar and the initial guess value of the attenuation value of the W-band radar are respectively obtained by the following formulas: to rain_Ka =0.01Z lin 0.63 to rain_W =0.14Z lin 0.44 Among them, Z lin is the linear representation of the absolute calibrated reflectivity factor, k rain_ka and k rain_W They represent the attenuation of Ka-band radar and W-band radar due to raindrops respectively.

5. The method according to claim 3, characterized in that: The initial guess value of the vertical motion is obtained by inverting the power spectrum of the Ka-band radar and the power spectrum of the W-band radar through a table lookup method, including: According to the theoretical Doppler spectrum ratio formula of Ka and W bands in the absence of air broadening, a lookup table of Doppler spectrum ratios corresponding to differential attenuation within a first preset range and air vertical motion within a second preset range is established; the lookup table is matched with the observed value of the Doppler spectrum ratio, and the obtained value of the air vertical motion is used as an initial guess of the air vertical motion.

6. The method according to claim 3, characterized in that The method of obtaining an initial guess value of the raindrop spectrum at the preset height by using a radar power spectrum inversion method according to the power spectrum of the Ka-band radar comprises: Obtaining a pre-inverted first raindrop spectrum using a radar power spectrum formula according to the power spectrum of the Ka-band radar; Performing gamma fitting on the first raindrop spectrum to obtain a second raindrop spectrum; The second raindrop spectrum is sampled to obtain an initial guess value of the raindrop spectrum.

7. A raindrop spectrum inversion device based on an optimal estimation model, characterized in that: include: A receiving module is used to obtain observation data of Ka-band radar, W-band radar and C-band radar at a preset altitude; An acquisition module, used to acquire an initial guess value of a raindrop spectrum parameter according to the observation data; the raindrop spectrum parameter includes a raindrop spectrum, an attenuation value of the Ka-band radar, an attenuation value of the W-band radar, and vertical air movement; A model module, used to establish an optimal estimation model based on raindrop inversion, wherein the optimal estimation model based on raindrop inversion includes a forward model based on raindrop inversion and a state variable, the input of the forward model based on raindrop inversion is an initial guess value of the state variable, and the output of the forward model based on raindrop inversion is a calculated value of the Ka-band radar power spectrum and a calculated value of the W-band radar power spectrum; An inversion module is used to take the initial guess value of the raindrop spectrum parameter and the preset air broadening spectrum width as the initial guess value of the state variable, and take the power spectrum observed by the Ka-band radar and the W-band radar and the reflectivity factor of the C-band after absolute calibration as the observation values ​​of the optimal estimation model based on raindrop inversion, and input them into the optimal estimation model based on raindrop inversion, so as to obtain the inversion result of the raindrops at the preset height output by the optimal estimation model based on raindrop inversion, wherein the inversion result includes the output value of the state variable.

8. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when being executed by a processor.

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