A method for spatio-temporal inversion of sea wave parameters using shipborne coherent S-band radar

Abstract

The present invention discloses a space-time inversion method for ocean wave parameters using a shipborne coherent S-band radar, comprising the following steps: obtaining a space-time Doppler spectrum and extracting the average Doppler frequency deviation; estimating a space-time radial velocity sequence and converting it into a wavenumber frequency spectrum; estimating the wavefield energy and group line energy distribution and designing an adaptive filter; filtering the wavenumber frequency spectrum and reconstructing a space-time radial Doppler velocity sequence; estimating the wavenumber directional spectrum; repeating the above process to obtain six wavenumber frequency spectra and inverting an undirected ocean wave spectrum; and finally inverting the ocean wave parameters. This method addresses the impact of breaking waves and ship motion on the accuracy of ocean wave parameter inversion. It not only retains the advantages of shore-based coherent microwave radar but also overcomes its shortcomings in spatial scalability and temporal continuity, significantly improving the robustness and accuracy of ocean wave parameter inversion using shipborne coherent S-band radar.

Description

Technical Field

[0001] The invention belongs to the technical field of microwave radar ocean remote sensing, and in particular relates to a space-time inversion method for ocean wave parameters using a shipborne coherent S-band radar. Background Art

[0002] In recent years, research on shipborne coherent microwave radar for marine environmental monitoring has begun. This radar not only retains the advantages of shore-based coherent microwave radar but also overcomes its shortcomings in spatial scalability and temporal continuity. Shipborne coherent microwave radar generates Bragg scattering by diffracting vertically polarized electromagnetic waves along the ocean surface, interacting with centimeter-waves on the ocean surface. This generates an echo Doppler spectrum that inverts the ocean surface state, allowing the extraction of a rich set of wave parameters, including wave height, wave period, and wave direction. Currently, wave parameter extraction primarily relies on inverting the wave height spectrum from the spatial-dimensional shipborne radar echo velocity sequence and then integrating the wave height spectrum. However, the modulation of breaking waves, which increases the low-frequency components in the wave height spectrum, and the energy shift of the wave height spectrum caused by ship motion, results in large errors in the estimated ocean parameters. Using spatial-dimensional velocity sequences cannot effectively remove the modulation of breaking waves or eliminate the influence of ship motion. Therefore, extracting wave parameters using spatial-dimensional velocity sequences has certain limitations and cannot accurately extract wave parameters. In order to broaden the detection range of ocean waves and improve the accuracy of wave parameter extraction, the space-time dimensional shipborne radar ocean echo velocity sequence is used to invert the wave parameters. Summary of the Invention

[0003] In view of the shortcomings of the existing technology, the present invention provides a space-time inversion method for ocean wave parameters using shipborne coherent S-band radar, which is used to solve the problem of accuracy of ocean wave parameter inversion by shipborne coherent S-band radar and the problem that the performance is affected by breaking waves and ship motion. The method specifically includes the following steps:

[0004] Step 1: The original echo data obtained by the shipborne coherent S-band radar is processed by the first FFT range transform and the second FFT Doppler transform to obtain the spatial-temporal Doppler spectrum of the ocean echo to be processed. Then, the average Doppler frequency deviation f of the antenna echo Doppler spectrum in each direction is extracted by the moment estimation method. d ;

[0005] Step 2: The average Doppler frequency shift f d Estimate the space-time radial Doppler velocity sequence v(r,t,β n ), and use 2D fast Fourier transform to transform the 2D velocity sequence v(r,t,β n ) is converted into a wavenumber frequency spectrum V r (k,f,β n );

[0006] Step 3: Use the least squares fitting algorithm to estimate the position parameters of the wave field energy distribution in the wave number frequency spectrum and the slope parameter s of the group line energy distribution g , and combine these two parameters to design a two-dimensional binary adaptive filter h a (k,f);

[0007] Step 4: Wavenumber frequency spectrum V r (k,f,β n ) filter to obtain the wavenumber frequency spectrum V after filtering a (k,f,β n ), the wavenumber frequency spectrum V after filtering a (k,f,β n ) performs two-dimensional inverse fast Fourier transform to reconstruct the space-time radial Doppler velocity sequence v a (r,t,β n );

[0008] Step 5: Perform fast Fourier transform on the spatial radial Doppler velocity sequence to obtain the energy spectrum G v (k,β n ), the wave number direction spectrum S(k,β n );

[0009] Step 6: Six shipborne radar antennas pointing to different sea surfaces obtain radar ocean echoes in different directions. Combine the radar ocean echoes in different directions and repeat steps 1 to 5 to synthesize these six wave number direction spectra into an undirected ocean wave spectrum S(f);

[0010] Step 7, calculate the effective wave height Hs and average wave period Tav through the first-order and second-order moments.

[0011] Moreover, in step 1, the moment estimation method is used to extract the average Doppler frequency deviation of the antenna echo Doppler spectrum in each direction. First, the ocean echo space-time Doppler spectrum peak is searched through the spectrum peak, and then the left and right frequency deviations f at 18dB of the spectrum peak are searched. l and f r Finally, the average Doppler frequency deviation f is extracted by moment estimation method d ,Right now:

[0012]

[0013] Where f is the Doppler frequency and σ is the Doppler spectrum.

[0014] Moreover, the space-time radial Doppler velocity sequence v(r, t, β n ) is determined by the average Doppler frequency shift f d The specific calculation method is as follows:

[0015]

[0016] Where λ is the electromagnetic wavelength, β n Indicates the nth th is the pointing direction of the root antenna, r is the radial distance, and t is the sampling time.

[0017] The 2D velocity sequence v(r,t,β n ) is converted into a wavenumber frequency spectrum V r (k,f,β n ),Right now:

[0018] V r (k,f,β n )=2DFFT[v(r,t,β n )] (3)

[0019] Where k is the wave number, f is the Doppler frequency, β n Indicates the nth th is the pointing direction of the root antenna, r is the radial distance, t is the sampling time, and 2DFFT represents two-dimensional fast Fourier transform.

[0020] Moreover, the least squares fitting algorithm in step 3 seeks the best function matching of the data by minimizing the sum of squares of the errors. Due to the influence of the forward speed of the ship, the wave field energy distribution no longer follows the first-order wave dispersion relation ω. 2 = gk, using the least squares fitting algorithm to estimate the position parameters of the wave field energy distribution in the wave number frequency spectrum It is estimated along the following formula:

[0021]

[0022] Where ω is the wave angular frequency, k is the wave number, is the angle between the antenna pointing direction and the forward motion direction of the ship, and g is the acceleration due to gravity.

[0023] Estimate the slope parameter s of the group line energy distribution using the least squares fitting algorithm g , fitting the distribution of group line energy, namely:

[0024] ω=s g k (5)

[0025] Where ω is the wave angular frequency, k is the wave number, and s is the wave frequency. g is the slope of the group line.

[0026] Combining the distribution of wave field energy and group line energy, a two-dimensional binary adaptive filter h is designed that can not only filter out the group line energy in the wave number frequency spectrum but also retain the wave field energy.a (k,f), that is:

[0027]

[0028] Where s g is the slope of the group line energy distribution, k is the wave number, g is the gravitational acceleration, f is the Doppler frequency, is the position parameter of the wave field energy distribution in the wavenumber frequency spectrum.

[0029] Moreover, the wavenumber frequency spectrum V after filtering in step 4 is a (k,f,β n ) is calculated as follows:

[0030] V a (k,f,β n )=V r (k,f,β n )·h a (7)

[0031] Where h a is the adaptive filter, V r (k,f,β n ) is the wavenumber frequency spectrum.

[0032] The wavenumber frequency spectrum V after filtering a (k,f,β n ) performs two-dimensional inverse fast Fourier transform to reconstruct the space-time radial Doppler velocity sequence v a (r,t,β n ),Right now:

[0033] v a (r,t,β n )=2DIFFT[V a (k,f,β n )] (8)

[0034] Where 2DIFFT represents two-dimensional inverse fast Fourier transform.

[0035] Moreover, in step 5, the space-dimensional velocity sequence is subjected to fast Fourier transform to obtain the energy spectrum G v (k,β n ), the specific calculation method is as follows:

[0036]

[0037] Where, t begin , t end and t number are the start time, end time and number of sampling points respectively, and FFT stands for fast Fourier transform.

[0038] The wave number direction spectrum S(k,β n ):

[0039] S(k,β n )=TF·G v (k,β n ) (10)

[0040] Where TF is the transfer function, and the specific calculation method is:

[0041]

[0042] Where tanh 2 is a hyperbolic function, k is the wave number, d is the water depth, g is the acceleration of gravity, N is the number of spatial sampling points, Δk and Δβ are the wave number resolution and angular resolution respectively, and θ is the antenna incident angle.

[0043] Moreover, the six wave number direction spectra are first synthesized into a wave number dimension undirected wave spectrum S(k), namely:

[0044]

[0045] Where, S(k,β n ) is the wave number directional spectrum, Δβ is the angular resolution;

[0046] Then, the frequency-dimensional undirected wave spectrum S(f) is obtained from the conversion relationship between the wavenumber dimension and the frequency dimension, that is:

[0047]

[0048] Where f is the wave frequency and k is the wave number.

[0049] Moreover, in step 7, the first-order and second-order moments are used to calculate the effective wave height Hs and the average wave period Tav. The specific calculation method is as follows:

[0050]

[0051] Where S(f) is the undirected wave spectrum and f is the wave frequency.

[0052] Compared with the prior art, the present invention has the following advantages:

[0053] 1) Based on the position of wave field energy and group line energy, an adaptive filter is designed to suppress the "group line" phenomenon that leads to inaccurate wave parameter estimation. The filter can also be adaptively adjusted according to the different ship speeds, which can adapt to the inversion of wave parameters at different ship speeds and meet the wave parameters of different navigation conditions under the ship-borne platform.

[0054] 2) The influence of breaking waves and ship motion on the accuracy of wave parameter inversion is solved. It not only retains the advantages of shore-based coherent microwave radar, but also makes up for the shortcomings of shore-based coherent microwave radar in spatial scalability and temporal continuity, greatly improving the robustness and accuracy of ship-borne coherent S-band radar wave parameter inversion. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 Flowchart of an embodiment of the present invention.

[0056] Figure 2 This is a comparison chart of the simulation results of the undirected wave spectrum inverted by the shipborne coherent S-band radar ocean echo at a ship speed of 10 knots simulated by the present invention and the theoretical wave spectrum.

[0057] Figure 3 This is a comparison chart of the measured results of the undirected wave spectrum and the buoy wave spectrum obtained by space-time inversion of wave parameters using shipborne coherent S-band radar.

[0058] Figure 4 This is a comparison chart of the effective wave height and average wave period sequence results inverted by the space-time inversion method of ocean wave parameters using shipborne coherent S-band radar measured in the present invention. DETAILED DESCRIPTION

[0059] The present invention provides a space-time inversion method for ocean wave parameters using a shipborne coherent S-band radar. The method solves the influence of breaking waves and ship motion on the accuracy of ocean wave parameter inversion. It not only retains the advantages of shore-based coherent microwave radar, but also makes up for the shortcomings of shore-based coherent microwave radar in spatial scalability and temporal continuity, greatly improving the robustness and accuracy of ocean wave parameter inversion by shipborne coherent S-band radar.

[0060] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0061] like Figure 1 As shown, the present invention provides a space-time inversion method for ocean wave parameters using a shipborne coherent S-band radar, comprising the following steps:

[0062] Step 1: The original echo data obtained by the shipborne coherent S-band radar is processed by the first FFT range transform and the second FFT Doppler transform to obtain the spatial-temporal Doppler spectrum of the ocean echo to be processed. Then, the average Doppler frequency deviation f of the antenna echo Doppler spectrum in each direction is extracted by the moment estimation method. d .

[0063] The average Doppler frequency deviation of the antenna echo Doppler spectrum in each direction is extracted by using the moment estimation method. First, the ocean echo space-time Doppler spectrum peak is searched through the spectrum peak, and then the left and right frequency deviations f at 18dB of the spectrum peak are searched.l and f r Finally, the average Doppler frequency deviation f is extracted by moment estimation method d ,Right now:

[0064]

[0065] Where f is the Doppler frequency and σ is the Doppler spectrum.

[0066] Step 2: The average Doppler frequency shift f d Estimate the space-time radial Doppler velocity sequence v(r,t,β n ), and the 2D velocity sequence v(r,t,β n ) is converted into a wavenumber frequency spectrum V r (k,f,β n ).

[0067] The radial Doppler velocity sequence v(r,t,β n ) is determined by the average Doppler frequency shift f d The specific calculation method is as follows:

[0068]

[0069] Where λ is the electromagnetic wavelength, β n Indicates the nth th is the pointing direction of the root antenna, r is the radial distance, and t is the sampling time.

[0070] The 2D velocity series is converted into a wavenumber frequency spectrum V using 2D Fast Fourier Transform (2-D FFT) r (k,f,β n ),Right now:

[0071] V r (k,f,β n )=2DFFT[v(r,t,β n )] (3)

[0072] Where k is the wave number, f is the Doppler frequency, β n Indicates the nth th is the pointing direction of the root antenna, r is the radial distance, and t is the sampling time.

[0073] Step 3: Use the least squares fitting algorithm to estimate the position parameters of the wave field energy distribution in the wave number frequency spectrum and the slope parameter s of the group line energy distribution g , and combining these two parameters to design a two-dimensional binary adaptive filter h that filters out the group line energy in the wavenumber frequency spectrum and retains the wave field energy a (k,f).

[0074] The least squares fitting algorithm finds the best function matching the data by minimizing the sum of squares of the errors. Due to the influence of the forward speed of the ship, the energy distribution of the wave field no longer follows the first-order wave dispersion relation (ω 2 =gk), and the least squares fitting algorithm is used to estimate the position parameters of the wave field energy distribution in the wave number frequency spectrum. It is estimated along the following formula:

[0075]

[0076] Where ω is the wave angular frequency, k is the wave number, is the angle between the antenna pointing direction and the forward motion direction of the ship, and g is the acceleration due to gravity.

[0077] Estimate the slope parameter s of the group line energy distribution using the least squares fitting algorithm g , fitting the distribution of group line energy, namely:

[0078] ω=s g k (5)

[0079] Where ω is the wave angular frequency, k is the wave number, and s is the wave frequency. g is the slope of the group line.

[0080] Combining the distribution of wave field energy and group line energy, a two-dimensional binary adaptive filter h is designed that can not only filter out the group line energy in the wave number frequency spectrum but also retain the wave field energy. a (k,f), that is:

[0081]

[0082] Where s g is the slope of the group line energy distribution, k is the wave number, and g is the acceleration of gravity.

[0083] Step 4: Wavenumber frequency spectrum V r (k,f,β n ) filter to obtain the wavenumber frequency spectrum V after filtering a (k,f,β n ), the wavenumber frequency spectrum V after filtering a (k,f,β n ) to perform two-dimensional inverse fast Fourier transform (2-D IFFT) to reconstruct the space-time radial Doppler velocity sequence v a (r,t,β n ).

[0084] Wavenumber frequency spectrum V after filtering a (k,f,β n ) is calculated as follows:

[0085] V a (k,f,β n )=V r (k,f,β n )·h a (7)

[0086] Where h a is the adaptive filter, V r (k,f,β n ) is the wavenumber frequency spectrum.

[0087] The wavenumber frequency spectrum V after filtering a (k,f,β n ) performs two-dimensional inverse fast Fourier transform (2-D FFT) to reconstruct the space-time radial Doppler velocity sequence v a (r,t,β n ),Right now:

[0088] v a (r,t,β n )=2DIFFT[V a (k,f,β n )] (8)

[0089] Step 5: Perform fast Fourier transform on the spatial radial Doppler velocity sequence to obtain the energy spectrum G v (k,β n ), the wave number direction spectrum S(k,β n ).

[0090] Perform fast Fourier transform on the spatial velocity sequence to obtain the energy spectrum G v (k,β n ), the specific calculation method is as follows:

[0091]

[0092] Where, t begin , t end and t number are the start time, end time and sampling time points respectively.

[0093] The wave number direction spectrum S(k,β n ):

[0094] S(k,β n )=TF·G v (k,β n ) (10)

[0095] Where TF is the transfer function, and the specific calculation method is:

[0096]

[0097] Where tanh 2 is a hyperbolic function, k is the wave number, d is the water depth, g is the acceleration of gravity, N is the number of spatial sampling points, Δk and Δβ are the wave number resolution and angular resolution respectively, and θ is the antenna incident angle.

[0098] In step 6, six shipborne radar antennas pointing to different sea surfaces obtain radar ocean echoes in different directions. Combine the radar ocean echoes in different directions and repeat steps 1 to 5 to synthesize these six wave number direction spectra into an undirected ocean wave spectrum S(f), i.e., the wave height spectrum.

[0099] Since the directional resolution of the antenna is 30°, each antenna can receive 30° of sea surface information in both the positive and negative directions of the sea surface. Therefore, six shipborne radar antennas pointing to different sea surfaces can obtain 360° of sea surface information, achieving omnidirectional coverage of sea surface information.

[0100] First, the six wave number direction spectra are synthesized into the wave number dimension undirected wave spectrum S(k), that is:

[0101]

[0102] Where, S(k,β n ) is the wavenumber directional spectrum, and Δβ is the angular resolution.

[0103] Then, the frequency-dimensional undirected wave spectrum S(f) is obtained from the conversion relationship between the wavenumber dimension and the frequency dimension, that is:

[0104]

[0105] Where f is the wave frequency and k is the wave number.

[0106] Step 7. Combined with the wave theory, calculate the effective wave height Hs and average wave period Tav through the first-order and second-order moments.

[0107] The first-order and second-order moments are used to calculate the effective wave height Hs and the average wave period Tav. The specific calculation method is as follows:

[0108]

[0109] Where S(f) is the undirected wave spectrum and f is the wave frequency.

[0110] Select wind speed of 12m / s, wind zone of 100km, wind direction of 0 degrees, ship speed of 10 knots, JONSWAP spectrum for undirected wave spectrum, and Longuet-Higgins spectrum for directed wave spectrum to generate simulated ocean echo Doppler spectrum. The results are as follows: Figure 2 As shown. Figure 2 It can be seen that the undirected ocean wave spectrum inverted by the method proposed in the present invention is highly consistent with the theoretical undirected ocean wave spectrum, and the inverted effective wave height (1.97m) and average wave period (5.34s) are very close to the theoretical values (1.96m and 5.39s).

[0111] The specific implementation of the present invention was applied to the inversion of ocean wave parameters measured by shipborne coherent S-band radar. The effectiveness of the present invention was verified by extracting the effective wave height and average wave period from the undirected ocean wave spectrum and comparing them with the effective wave height and wave period of the buoy. The undirected ocean wave spectrum of the measured buoy was compared with the undirected ocean wave spectrum obtained by the space-time inversion method of the ocean wave parameters measured by the shipborne coherent S-band radar at a certain moment. Figure 3 ,Depend on Figure 3 It can be seen that the significant wave height and average wave period extracted from the undirected wave spectrum inverted by the method proposed in this invention are close to the significant wave height and average wave period measured from the buoy. The significant wave height and average wave period inverted by 270 S-band radars for about 2 days are compared with the significant wave height and average wave period obtained from the buoy. Figure 4 The significant wave height and average wave period extracted by the proposed method are in good agreement with those of the buoy, with root mean square errors of 0.30 m and 0.35 s, and average errors of 0.24 m and 0.28 s, respectively.

[0112] The specific embodiments described herein are merely illustrative of the spirit of the present invention. Persons skilled in the art may make various modifications, additions, or substitutions to the described specific embodiments without departing from the spirit of the present invention or exceeding the scope of the appended claims.

Claims

1. A space-time inversion method for ocean wave parameters using shipborne coherent S-band radar, characterized in that: The following steps are involved: Step 1: The original echo data obtained by the shipborne coherent S-band radar is processed by the first FFT range transform and the second FFT Doppler transform to obtain the spatial-temporal Doppler spectrum of the ocean echo to be processed. Then, the average Doppler frequency deviation f of the antenna echo Doppler spectrum in each direction is extracted by the moment estimation method. d ; Step 2: The average Doppler frequency shift f d Estimate the space-time radial Doppler velocity sequence v(r,t,β n ), and use 2D fast Fourier transform to transform the 2D velocity sequence v(r,t,β n ) is converted into a wavenumber frequency spectrum V r (k,f,β n ); Step 3: Use the least squares fitting algorithm to estimate the position parameters of the wave field energy distribution in the wave number frequency spectrum and the slope parameter s of the group line energy distribution g , and combine these two parameters to design a two-dimensional binary adaptive filter h a (k,f); Step 4: Wavenumber frequency spectrum V r (k,f,β n ) filter to obtain the wavenumber frequency spectrum V after filtering a (k,f,β n ), the wavenumber frequency spectrum V after filtering a (k,f,β n ) performs two-dimensional inverse fast Fourier transform to reconstruct the space-time radial Doppler velocity sequence v a (r,t,β n ); Step 5: Perform fast Fourier transform on the spatial radial Doppler velocity sequence to obtain the energy spectrum G v (k,β n ), the wave number direction spectrum S(k,β n ); Step 6: Six shipborne radar antennas pointing to different sea surfaces obtain radar ocean echoes in different directions. Combine the radar ocean echoes in different directions and repeat steps 1 to 5 to synthesize these six wave number direction spectra into an undirected ocean wave spectrum S(f); Step 7, calculate the effective wave height Hs and average wave period Tav through the first-order and second-order moments.

2. The method for space-time inversion of ocean wave parameters using a shipborne coherent S-band radar according to claim 1, characterized in that: In step 1, the moment estimation method is used to extract the average Doppler frequency deviation of the antenna echo Doppler spectrum in each direction. First, the ocean echo space-time Doppler spectrum peak is searched through the spectrum peak, and then the left and right frequency deviations f at 18dB of the spectrum peak are searched. l and f r Finally, the average Doppler frequency deviation f is extracted by moment estimation method d ,Right now: Where f is the Doppler frequency and σ is the Doppler spectrum.

3. The method for space-time inversion of ocean wave parameters using a shipborne coherent S-band radar according to claim 1, characterized in that: Step 2: The spatial-time radial Doppler velocity sequence v(r, t, β n ) is determined by the average Doppler frequency shift f d The specific calculation method is as follows: Where λ is the electromagnetic wavelength, β n Indicates the nth th The pointing direction of the root antenna, r is the radial distance, and t is the sampling time; The 2D velocity sequence v(r,t,β n ) is converted into a wavenumber frequency spectrum V r (k,f,β n ),Right now: V r (k,f,β n )=2DFFT[v(r,t,β n )] (3) Where k is the wave number, f is the Doppler frequency, β n Indicates the nth th is the pointing direction of the root antenna, r is the radial distance, t is the sampling time, and 2DFFT represents two-dimensional fast Fourier transform.

4. The method for space-time inversion of ocean wave parameters using a shipborne coherent S-band radar according to claim 1, wherein: In step 3, the least squares fitting algorithm seeks the best function matching of the data by minimizing the sum of squares of the errors. Due to the influence of the forward speed of the ship, the energy distribution of the wave field no longer follows the first-order wave dispersion relation ω. 2 = gk, using the least squares fitting algorithm to estimate the position parameters of the wave field energy distribution in the wave number frequency spectrum It is estimated along the following formula: Where ω is the angular frequency of the waves, k is the wave number, g is the acceleration of gravity, It is the angle between the antenna pointing direction and the forward motion direction of the ship.

5. The method for space-time inversion of ocean wave parameters using shipborne coherent S-band radar according to claim 4, characterized in that: In step 3, the slope parameter s of the group line energy distribution is estimated using the least squares fitting algorithm. g , fitting the distribution of group line energy, namely: ω=s g k (5) Where ω is the wave angular frequency, k is the wave number, and s is the wave frequency. g is the slope of the group line; Combining the distribution of wave field energy and group line energy, a two-dimensional binary adaptive filter h is designed that can not only filter out the group line energy in the wave number frequency spectrum but also retain the wave field energy. a (k,f), that is: Where s g is the slope of the group line energy distribution, k is the wave number, g is the gravitational acceleration, f is the Doppler frequency, is the position parameter of the wave field energy distribution in the wavenumber frequency spectrum.

6. The method for space-time inversion of ocean wave parameters using shipborne coherent S-band radar according to claim 1, characterized in that: The wavenumber frequency spectrum V after filtering in step 4 a (k,f,β n ) is calculated as follows: V a (k,f,b n )=V r (k,f,b n )·h a (7) Where h a is the adaptive filter, V r (k,f,β n ) is the wavenumber frequency spectrum; The wavenumber frequency spectrum V after filtering a (k,f,β n ) performs two-dimensional inverse fast Fourier transform to reconstruct the space-time radial Doppler velocity sequence v a (r,t,β n ),Right now: v a (r,t,β n )=2DIFFT[V a (k,f,β n )] (8) Where 2DIFFT represents two-dimensional inverse fast Fourier transform.

7. The method for space-time inversion of ocean wave parameters using shipborne coherent S-band radar according to claim 1, characterized in that: In step 5, the fast Fourier transform of the spatial velocity sequence is performed to obtain the energy spectrum G v (k,β n ), the specific calculation method is as follows: Where, t begin , t end and t number are the start time, end time and number of sampling points respectively, and FFT stands for fast Fourier transform.

8. The method for space-time inversion of ocean wave parameters using shipborne coherent S-band radar according to claim 7, characterized in that: In step 5, the energy spectrum is used to estimate the wave number direction spectrum S(k,β n ): S(k,β n )=TF·G v (k,b n ) (10) Where TF is the transfer function, and the specific calculation method is: Where tanh 2 is a hyperbolic function, k is the wave number, d is the water depth, g is the acceleration of gravity, N is the number of spatial sampling points, Δk and Δβ are the wave number resolution and angular resolution respectively, and θ is the antenna incident angle.

9. The method for space-time inversion of ocean wave parameters using shipborne coherent S-band radar according to claim 1, characterized in that: In step 6, the six wave number direction spectra are first synthesized into the wave number dimension undirected wave spectrum S(k), that is: Where, S(k,β n ) is the wave number directional spectrum, Δβ is the angular resolution; Then, the frequency-dimensional undirected wave spectrum S(f) is obtained from the conversion relationship between the wavenumber dimension and the frequency dimension, that is: Where f is the wave frequency and k is the wave number.

10. The method for space-time inversion of ocean wave parameters using shipborne coherent S-band radar according to claim 1, characterized in that: In step 7, the first-order and second-order moments are used to calculate the effective wave height Hs and the average wave period Tav. The specific calculation method is as follows: Where S(f) is the undirected wave spectrum and f is the wave frequency.

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