CN116430337A - Sea wave parameter space-time inversion method using shipborne coherent S-band radar - Google Patents
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Abstract
The invention discloses a space-time inversion method for sea wave parameters by utilizing a shipborne coherent S-band radar, which comprises the following steps: acquiring a space-time Doppler spectrum and extracting average Doppler frequency offset; estimating a space-time dimensional radial velocity sequence and converting the space-time dimensional radial velocity sequence into a wave number frequency spectrum; estimating wave field energy and group line energy distribution and designing an adaptive filter; filtering the wave number frequency spectrum and reconstructing a space-time dimension radial Doppler velocity sequence; estimating a wave number direction spectrum; repeating the above process to obtain six wave number frequency spectrums and inverting the undirected wave spectrum; and (5) carrying out sea wave parameter inversion. The method solves the problem of influence of broken waves and ship motion on the sea wave parameter inversion precision, not only maintains the advantages of the shore-based coherent microwave radar, but also makes up the defects of the shore-based coherent microwave radar in spatial ductility and time continuity, and greatly improves the robustness and precision of sea wave parameter inversion of the ship-borne coherent S-band radar.
Description
Technical Field
The invention belongs to the technical field of ocean remote sensing of microwave radars, and particularly relates to a space-time inversion method for sea wave parameters by utilizing a shipborne coherent S-band radar.
Background
In recent years, the research of applying the shipborne coherent microwave radar to marine environment monitoring starts, not only the advantages of the shore-based coherent microwave radar are reserved, but also the defects of the shore-based coherent microwave radar in terms of spatial ductility and time continuity are overcome. The shipborne coherent microwave radar generates Bragg scattering through interaction of vertically polarized electromagnetic waves which are diffracted and propagated along the ocean surface and centimeter waves on the ocean surface, and obtains echo Doppler spectrum inverting the ocean surface state, so that rich wave parameters including wave height, wave period, wave direction and the like can be extracted. At present, the sea wave parameters are extracted mainly by utilizing a space-dimensional shipborne radar sea echo velocity sequence to invert the wave height spectrum, and then the wave height spectrum is integrated. However, due to the fact that the modulation effect of the broken waves can cause the increase of low-frequency components in the wave high spectrum and the shift of wave high-spectrum energy caused by the motion of the ship, the estimated ocean parameters have large estimation errors, the modulation of the broken waves cannot be well removed by using the space dimension speed sequence, the influence of the motion of the ship is eliminated, and therefore the fact that the sea wave parameters are extracted by using the space dimension speed sequence has a certain limitation and the sea wave parameters cannot be accurately extracted. In order to widen the detection range of the sea wave and improve the accuracy of sea wave parameter extraction, a space-time dimension ship-borne radar sea echo speed sequence is adopted to carry out sea wave parameter inversion.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a space-time inversion method for wave parameters by using a shipborne coherent S-band radar, which is used for solving the accuracy problem of the inversion of the wave parameters of the shipborne coherent S-band radar and the problem that the performance is influenced by broken waves and ship motions, and specifically comprises the following steps:
Step 3, estimating the position parameters of wave field energy distribution in the wave number frequency spectrum by adopting a least square fitting algorithm
And slope parameter s of group line energy distribution g And combining the two parameters to design a two-dimensional binary adaptive filter h a (k,f)；
and 7, calculating the effective wave height Hs and the average wave period Tav through the first-order moment and the second-order moment.
In addition, in the step 1, the average Doppler frequency offset of the Doppler spectrum of the antenna echo in each direction is extracted by utilizing a moment estimation method, firstly, the Doppler spectrum peak of the ocean echo space-time dimension is searched through the spectrum peak, and then, the left and right frequency offset f at 18dB of the spectrum peak is searched l And f r Finally, extracting average Doppler frequency offset f by a moment estimation method d The method comprises the following steps:
where f is the Doppler frequency and σ is the Doppler spectrum.
Furthermore, the step 2 is a hollow time-dimensional radial Doppler velocity sequence v (r, t, beta) n ) From the average Doppler frequency offset f d The specific calculation mode is as follows:
wherein lambda is the electromagnetic wavelength, beta n Represents the nth th The pointing direction of the root antenna, r is the radial distance, and t is the sampling time.
2-dimensional velocity sequence v (r, t, beta) using 2-dimensional fast fourier transform n ) Conversion to wave number frequency spectrum V r (k,f,β n ) The method comprises the following steps:
V r (k,f,β n )＝2DFFT[v(r,t,β n )] (3)
where k is the wave number, f is the Doppler frequency, beta n Represents the nth th The pointing direction of the root antenna, r is the radial distance, t is the sampling time, and 2DFFT represents the two-dimensional fast fourier transform.
Moreover, the least square fitting algorithm in the step 3 finds the best function matching of the data by minimizing the sum of squares of errors, and the wave field energy distribution is no longer along the first-order wave dispersion relation omega due to the influence of the forward speed of the ship 2 =gk, estimation of the position parameters of the wave field energy distribution in the wave number frequency spectrum using least squares fitting algorithm
It is estimated along the following formula:
wherein ω is the angular frequency of the ocean wave, k is the wave number of the ocean wave,
g is the gravity acceleration, which is the included angle between the pointing direction of the antenna and the forward motion direction of the ship.
Estimating slope parameter s of group line energy distribution by least square fitting algorithm g Fitting the distribution of group line energy, namely:
ω＝s g k (5)
wherein ω is the angular frequency of the ocean wave, k is the wave number of the ocean wave, s g Is the slope of the group line.
By combining the distribution positions of wave field energy and group line energy, a two-dimensional binary self-adaptive filter h capable of filtering the group line energy in the wave number frequency spectrum and retaining the wave field energy is designed a (k, f), namely:
wherein s is g Is the slope of the energy distribution of the group line, k is the wave number of sea waves, g is the gravitational acceleration, f is the Doppler frequency,
is a positional parameter of the wave field energy distribution in the wave number frequency spectrum.
Furthermore, the wave number frequency spectrum V after the filtering process in the step 4 a (k,f,β n ) The calculation method is as follows:
V a (k,f,β n )＝V r (k,f,β n )·h a (7)
in the formula, h a Is an adaptive filter, V r (k,f,β n ) Is the wavenumber frequency spectrum.
For wave number frequency spectrum V after filtering a (k,f,β n ) Reconstructing space-time-dimension radial Doppler velocity sequence v by two-dimensional inverse fast Fourier transform a (r,t,β n ) The method comprises the following steps:
v a (r,t,β n )＝2DIFFT[V a (k,f,β n )] (8)
where 2DIFFT represents a two-dimensional inverse fast fourier transform.
And, in the step 5, the space-dimensional velocity sequence is subjected to fast Fourier transform to obtain an energy spectrum G v (k,β n ) The specific calculation mode is as follows:
wherein t is begin 、t end And t number The number of points, respectively start time, end time and sample time, the FFT represents the fast fourier transform.
Estimating wavenumber direction spectrum S (k, β) from energy spectrum by transfer function TF n )：
S(k,β n )＝TF·G v (k,β n ) (10)
Wherein, TF is a conversion function, and the specific calculation mode is as follows:
in the formula, tanh 2 And k is the wave number of the sea wave, d is the water depth, g is the gravitational acceleration, N is the number of space sampling points, deltak and Deltaβ are the wave number resolution and the angle resolution respectively, and theta is the antenna incident angle.
And, the six wave number direction spectrums are synthesized into a wave number-dimensional undirected wave spectrum S (k), namely:
wherein S (k, beta) n ) Is wave number direction spectrum, delta beta is angular resolution;
and then obtaining the undirected wave spectrum S (f) of the frequency dimension according to the conversion relation of the undirected wave spectrum of the wave number dimension and the frequency dimension, namely:
wherein f is the wave frequency and k is the wave number.
In addition, in the step 7, the effective wave height Hs and the average wave period Tav are calculated by using the first-order moment and the second-order moment, and the specific calculation method is as follows:
wherein S (f) is undirected wave spectrum, and f is wave frequency.
Compared with the prior art, the invention has the following advantages:
1) According to the positions of wave field energy and group line energy, the self-adaptive filter is designed to inhibit the phenomenon of 'group line' which leads to inaccurate wave parameter estimation, and the filter can be adaptively adjusted according to different ship speeds of ships, so that the wave parameter inversion of different ship speeds can be adapted, and the wave parameters of different navigation conditions under a ship-borne platform are met.
2) The method solves the problem that the broken wave and the ship motion affect the sea wave parameter inversion precision, not only maintains the advantages of the shore-based coherent microwave radar, but also makes up the defects of the shore-based coherent microwave radar in spatial ductility and time continuity, and greatly improves the robustness and the precision of sea wave parameter inversion of the ship-borne coherent S-band radar.
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FIG. 1 is a flow chart of an embodiment of the present invention.
Fig. 2 is a diagram showing a comparison of simulation results of a ship-borne coherent S-band radar ocean echo inversion undirected wave spectrum and a theoretical wave spectrum with a ship speed of 10 knots.
FIG. 3 is a graph of actual measurement results of the space-time inversion of the undirected wave spectrum and the buoy wave spectrum of the wave parameter by using the shipborne coherent S-band radar.
Fig. 4 is a graph showing the comparison of the actual measured results of the effective wave height and average wave period sequences of the inversion of the space-time inversion method of the wave parameters by using the shipborne coherent S-band radar.
Detailed Description
The invention provides a space-time inversion method for wave parameters by utilizing a shipborne coherent S-band radar, which solves the problem of influence of broken waves and ship motion on the inversion precision of the wave parameters, not only maintains the advantages of a shore-based coherent microwave radar, but also can make up the defects of the shore-based coherent microwave radar in spatial ductility and time continuity, and greatly improves the robustness and the precision of the shipborne coherent S-band radar wave parameter inversion.
The technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
As shown in fig. 1, the invention provides a space-time inversion method for sea wave parameters by using a shipborne coherent S-band radar, which comprises the following steps:
Extracting average Doppler frequency offset of antenna echo Doppler spectrum in each direction by using a moment estimation method, searching ocean echo space-time dimension Doppler spectrum peak through spectrum peak, and searching left and right frequency offset f at 18dB of spectrum peak l And f r Finally, extracting average Doppler frequency offset f by a moment estimation method d The method comprises the following steps:
where f is the Doppler frequency and σ is the Doppler spectrum.
Space-time dimension radial Doppler velocity sequence v (r, t, beta) n ) From the average Doppler frequency offset f d The specific calculation mode is as follows:
wherein lambda is the electromagnetic wavelength, beta n Represents the nth th The pointing direction of the root antenna, r is the radial distance, and t is the sampling time.
Converting 2-dimensional velocity sequences into wavenumber frequency spectra V using 2-dimensional fast Fourier transforms (2-D FFT) r (k,f,β n ) The method comprises the following steps:
V r (k,f,β n )＝2DFFT[v(r,t,β n )] (3)
where k is the wave number, f is the Doppler frequency, beta n Represents the nth th The pointing direction of the root antenna, r is the radial distance, and t is the sampling time.
Step 3, estimating the position parameters of wave field energy distribution in the wave number frequency spectrum by adopting a least square fitting algorithm
And slope parameter s of group line energy distribution g And combining the two parameters to design a two-dimensional binary adaptive filter h for filtering out group line energy in the wave number frequency spectrum and retaining wave field energy a (k,f)。
The least squares fitting algorithm finds the best functional match for the data by minimizing the sum of squares of the errors. The energy distribution of the field due to the influence of the forward speed of the ship is no longer along the first order wave dispersion relation (omega 2 =gk) estimating the position parameters of the wave field energy distribution in the wave number frequency spectrum using least squares fitting algorithm
It is estimated along the following formula:
wherein ω is the angular frequency of the ocean wave, k is the wave number of the ocean wave,
g is the gravity acceleration, which is the included angle between the pointing direction of the antenna and the forward motion direction of the ship.
Estimating slope parameter s of group line energy distribution by least square fitting algorithm g Fitting the distribution of group line energy, namely:
ω＝s g k (5)
wherein ω is the angular frequency of the ocean wave, k is the wave number of the ocean wave, s g Is the slope of the group line.
By combining the distribution positions of wave field energy and group line energy, a two-dimensional binary self-adaptive filter h capable of filtering the group line energy in the wave number frequency spectrum and retaining the wave field energy is designed a (k, f), namely:
wherein s is g The slope of the energy distribution of the group line is that k is wave number of sea waves and g is gravity acceleration.
Wave number frequency spectrum V after filtering a (k,f,β n ) The calculation method is as follows:
V a (k,f,β n )＝V r (k,f,β n )·h a (7)
in the formula, h a Is self-containedAdaptive filter, V r (k,f,β n ) Is the wavenumber frequency spectrum.
For wave number frequency spectrum V after filtering a (k,f,β n ) Reconstructing a space-time-dimensional radial Doppler velocity sequence v by performing two-dimensional inverse fast Fourier transform (2-D FFT) a (r,t,β n ) The method comprises the following steps:
v a (r,t,β n )＝2DIFFT[V a (k,f,β n )] (8)
Performing fast Fourier transform on the space-dimensional velocity sequence to obtain an energy spectrum G v (k,β n ) The specific calculation mode is as follows:
wherein t is begin 、t end And t number The number of points is the start time, the end time and the sampling time, respectively.
Estimating wavenumber direction spectrum S (k, beta) from energy spectrum through conversion relation TF n )：
S(k,β n )＝TF·G v (k,β n ) (10)
Wherein, TF is a conversion function, and the specific calculation mode is as follows:
in the formula, tanh 2 And k is the wave number of the sea wave, d is the water depth, g is the gravitational acceleration, N is the number of space sampling points, deltak and Deltaβ are the wave number resolution and the angle resolution respectively, and theta is the antenna incident angle.
And 6, obtaining radar ocean echoes in different directions by six shipborne radar antennas pointing to different sea surfaces, combining the radar ocean echoes in different directions, repeatedly executing the steps 1-5, and synthesizing the six wave number direction spectrums into an undirected wave spectrum S (f), namely a wave height spectrum.
Because the directional resolution of the antennas is 30 degrees, each antenna can receive sea surface information of 30 degrees in the forward and reverse directions of the sea surface, and therefore six shipborne radar antennas pointing to different sea surfaces can obtain 360 degrees of sea surface information, and omni-directional coverage of the sea surface information is achieved.
Firstly, synthesizing a wave number-dimensional undirected wave spectrum S (k) from six wave number direction spectrums, namely:
wherein S (k, beta) n ) Is the wavenumber direction spectrum, Δβ is the angular resolution.
And then obtaining the undirected wave spectrum S (f) of the frequency dimension according to the conversion relation of the undirected wave spectrum of the wave number dimension and the frequency dimension, namely:
wherein f is the wave frequency and k is the wave number.
And 7, calculating the effective wave height Hs and the average wave period Tav through the first-order moment and the second-order moment by combining the wave theory.
The effective wave height Hs and the average wave period Tav are calculated by using the first-order moment and the second-order moment, and the specific calculation mode is as follows:
wherein S (f) is undirected wave spectrum, and f is wave frequency.
The wind speed value is 12m/s, the wind area is 100km, the wind direction is 0 degree, the ship speed is 10 knots, the undirected sea wave spectrum type is a JONSWAP spectrum, the directed sea wave spectrum is a Longuet-Higgins spectrum, and a simulated sea echo Doppler spectrum is generated, and the result is shown in figure 2. As can be seen from FIG. 2, the undirected wave spectrum obtained by inversion of the method provided by the invention has very high coincidence degree with the theoretical undirected wave spectrum, and the effective wave height (1.97 m) and the average wave period (5.34 s) of the inversion are very close to the theoretical values (1.96 m and 5.39 s).
The specific implementation mode of the invention is applied to the sea wave parameter inversion of the actual measurement shipborne coherent S-band radar, and the effectiveness of the invention is verified by extracting the effective wave height and the average wave period from the undirected sea wave spectrum and comparing the effective wave height and the wave period of the buoy. The result pair of the undirected wave spectrum of the actual measurement buoy and the undirected wave spectrum obtained by inversion of the ocean wave parameter space-time inversion method of the actual measurement shipborne coherent S-band radar at a certain moment is shown in fig. 3, and as can be seen from fig. 3, the period of extracting effective wave height and average wave from the undirected wave spectrum inverted by the method provided by the invention is close to the period of effective wave height and average wave measured from the buoy. The effective wave height and average wave period of the 270S-band radar inversion for approximately 2 days was compared to the effective wave height and average wave period acquired by the buoy, as shown in fig. 4. The effective wave height and average wave period extracted by the method are well matched with the buoy, the root mean square error is 0.30m and 0.35s respectively, and the average error is 0.24m and 0.28s respectively.
The specific embodiments described herein are offered by way of example only to illustrate the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Claims (10)
1. A sea wave parameter space-time inversion method using a ship-borne coherent S-band radar is characterized by comprising the following steps:
step 1, original echo data acquired by a ship-borne coherent S-band radar sequentially pass through first FFT distance conversion processing and second FFT Doppler conversion processing to obtain to-be-processed echo dataThe space-time dimension Doppler spectrum of the ocean echo is extracted, and then the average Doppler frequency offset f of the antenna echo Doppler spectrum in all directions is extracted by a moment estimation method d ；
Step 2, by average Doppler frequency offset f d Estimating a space-time dimensional radial Doppler velocity sequence v (r, t, beta) n ) And 2-dimensional velocity sequences v (r, t, beta) are transformed using a 2-dimensional fast fourier transform n ) Conversion to wave number frequency spectrum V r (k,f,β n )；
Step 3, estimating the position parameters of wave field energy distribution in the wave number frequency spectrum by adopting a least square fitting algorithm
And slope parameter s of group line energy distribution g And combining the two parameters to design a two-dimensional binary adaptive filter h a (k,f)；
Step 4, for wave number frequency spectrum V r (k,f,β n ) Filtering to obtain wave number frequency spectrum V after filtering a (k,f,β n ) For the wave number frequency spectrum V after filtering a (k,f,β n ) Reconstructing space-time-dimension radial Doppler velocity sequence v by two-dimensional inverse fast Fourier transform a (r,t,β n )；
Step 5, performing fast Fourier transform on the space-dimensional radial Doppler velocity sequence to obtain an energy spectrum G v (k,β n ) Estimating wave number direction spectrum S (k, β) from energy spectrum by conversion function n )；
Step 6, six shipborne radar antennas pointing to different sea surfaces are used for obtaining radar ocean echoes in different directions, the radar ocean echoes in different directions are combined, the steps 1-5 are repeatedly executed, and the six wave number direction spectrums are synthesized into an undirected wave spectrum S (f);
and 7, calculating the effective wave height Hs and the average wave period Tav through the first-order moment and the second-order moment.
2. A method of space-time inversion of sea wave parameters using a coherent S-band radar on board a vessel as claimed in claim 1, wherein: in step 1, moment estimation method is used for extractionThe average Doppler frequency offset of the Doppler spectrum of the antenna echo in each direction is firstly searched for the Doppler spectrum peak of the ocean echo space-time dimension through the spectrum peak, and then the left and right frequency offset f at 18dB of the spectrum peak is searched for l And f r Finally, extracting average Doppler frequency offset f by a moment estimation method d The method comprises the following steps:
where f is the Doppler frequency and σ is the Doppler spectrum.
3. A method of space-time inversion of sea wave parameters using a coherent S-band radar on board a vessel as claimed in claim 1, wherein: step 2 hollow time-dimensional radial Doppler velocity sequence v (r, t, beta) n ) From the average Doppler frequency offset f d The specific calculation mode is as follows:
wherein lambda is the electromagnetic wavelength, beta n Represents the nth th The pointing direction of the root antenna, r is the radial distance, and t is the sampling time;
2-dimensional velocity sequence v (r, t, beta) using 2-dimensional fast fourier transform n ) Conversion to wave number frequency spectrum V r (k,f,β n ) The method comprises the following steps:
V r (k,f,β n )＝2DFFT[v(r,t,β n )] (3)
where k is the wave number, f is the Doppler frequency, beta n Represents the nth th The pointing direction of the root antenna, r is the radial distance, t is the sampling time, and 2DFFT represents the two-dimensional fast fourier transform.
4. A method of space-time inversion of sea wave parameters using a coherent S-band radar on board a vessel as claimed in claim 1, wherein: least square fitting algorithm in step 3Finding the best function match of the data by minimizing the sum of squares of the errors, the wave field energy distribution no longer follows the first order wave dispersion relationship ω due to the influence of the forward speed of the vessel 2 =gk, estimation of the position parameters of the wave field energy distribution in the wave number frequency spectrum using least squares fitting algorithm
It is estimated along the following formula:
wherein ω is the angular frequency of sea wave, k is the wave number of sea wave, g is the gravitational acceleration,
the angle between the pointing direction of the antenna and the forward motion direction of the ship.
5. The space-time inversion method for sea wave parameters by using shipborne coherent S-band radar according to claim 4, wherein: in step 3, the slope parameter s of the energy distribution of the group line is estimated by utilizing a least square fitting algorithm g Fitting the distribution of group line energy, namely:
ω＝s g k (5)
wherein ω is the angular frequency of the ocean wave, k is the wave number of the ocean wave, s g Is the slope of the group line;
by combining the distribution positions of wave field energy and group line energy, a two-dimensional binary self-adaptive filter h capable of filtering the group line energy in the wave number frequency spectrum and retaining the wave field energy is designed a (k, f), namely:
wherein s is g Is the slope of the energy distribution of the group line, k is the wave number of sea waves,g is the gravity acceleration, f is the Doppler frequency,
is a positional parameter of the wave field energy distribution in the wave number frequency spectrum.
6. A method of space-time inversion of sea wave parameters using a coherent S-band radar on board a vessel as claimed in claim 1, wherein: wave number frequency spectrum V after filtering in step 4 a (k,f,β n ) The calculation method is as follows:
V a (k,f,β n )＝V r (k,f,β n )·h a (7)
in the formula, h a Is an adaptive filter, V r (k,f,β n ) Is wave number frequency spectrum;
for wave number frequency spectrum V after filtering a (k,f,β n ) Reconstructing space-time-dimension radial Doppler velocity sequence v by two-dimensional inverse fast Fourier transform a (r,t,β n ) The method comprises the following steps:
v a (r,t,β n )＝2DIFFT[V a (k,f,β n )] (8)
where 2DIFFT represents a two-dimensional inverse fast fourier transform.
7. A method of space-time inversion of sea wave parameters using a coherent S-band radar on board a vessel as claimed in claim 1, wherein: in step 5, performing fast Fourier transform on the space-dimensional velocity sequence to obtain an energy spectrum G v (k,β n ) The specific calculation mode is as follows:
wherein t is begin 、t end And t number The number of points, respectively start time, end time and sample time, the FFT represents the fast fourier transform.
8. The space-time inversion method for sea wave parameters by using shipborne coherent S-band radar according to claim 7, wherein: estimating wave number direction spectrum S (k, beta) from energy spectrum by transfer function TF in step 5 n )：
S(k,β n )＝TF·G v (k,β n ) (10)
Wherein, TF is a conversion function, and the specific calculation mode is as follows:
in the formula, tanh 2 And k is the wave number of the sea wave, d is the water depth, g is the gravitational acceleration, N is the number of space sampling points, deltak and Deltaβ are the wave number resolution and the angle resolution respectively, and theta is the antenna incident angle.
9. A method of space-time inversion of sea wave parameters using a coherent S-band radar on board a vessel as claimed in claim 1, wherein: in the step 6, firstly, synthesizing a wave number dimensional undirected wave spectrum S (k) from the six wave number direction spectrums, namely:
wherein S (k, beta) n ) Is wave number direction spectrum, delta beta is angular resolution;
and then obtaining the undirected wave spectrum S (f) of the frequency dimension according to the conversion relation of the undirected wave spectrum of the wave number dimension and the frequency dimension, namely:
wherein f is the wave frequency and k is the wave number.
10. A method of space-time inversion of sea wave parameters using a coherent S-band radar on board a vessel as claimed in claim 1, wherein: in the step 7, the effective wave height Hs and the average wave period Tav are calculated by using the first-order moment and the second-order moment, and the specific calculation mode is as follows:
wherein S (f) is undirected wave spectrum, and f is wave frequency.
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| CN (1) | CN116430337A (en) |
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2023
- 2023-03-15 CN CN202310265278.0A patent/CN116430337A/en active Pending
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