CN104101864A - Inversion Algorithm of Ocean Wave Parameters Based on EOF Decomposition for Navigation X-band Radar - Google Patents

Abstract

The present invention relates to a navigation X-band radar sea wave parameter inversion algorithm based on EOF decomposition, which comprises the following steps: first, EOF decomposition is performed on navigation X-band radar image sequences to obtain different modes; then the Burg algorithm is used to obtain the principal component of the first mode The maximum entropy power spectrum, according to the peak of the spectrum to obtain the period and wavelength of the ocean wave; use the linear relationship between the standard deviation of the principal component of a mode and the effective wave height to obtain the effective wave height of the ocean wave; use the space function of the first mode and the principal component weight Construct the radar image sequence of the first mode of the wave field, perform two-dimensional Fourier transform on any image in the sequence, and determine the quasi-wave direction according to the peak value of the wave number spectrum obtained; use the similarity of wave stripes in two adjacent radar images to determine the wave direction. The invention utilizes EOF to decompose the ocean wave field into different modes, and extracts the wave height, period, wavelength and wave direction of the ocean waves from the main modes, thereby solving the inhomogeneity of the wave field and the influence of high noise in low sea conditions.

Description

Inversion Algorithm of Ocean Wave Parameters Based on EOF Decomposition for Navigation X-band Radar

technical field

The invention belongs to the technical field of marine remote sensing, and relates to a navigation X-band radar sea wave parameter inversion algorithm based on EOF decomposition.

Background technique

Waves have an important impact on people's production and life. For example, the construction of near-shore port channels, fishery production, and the navigation of ships in the ocean are closely related to waves. Therefore, ocean wave observation has important practical significance. Traditional observation methods such as buoys can accurately obtain information on changes in ocean waves, but they can only obtain changes in ocean waves at fixed points, and are not easy to manage and maintain. Navigation X-band radar is an all-weather and all-weather high-resolution imaging radar, which can be used to extract information such as wave height, period, wavelength and wave direction of ocean waves from sea clutter images.

Existing methods for inverting ocean wave parameters from navigational X-band radar image sequences are mainly based on ocean wave spectra. Firstly, three-dimensional Fourier transform is performed on the radar image sequence to obtain the radar image spectrum, and then the radar image spectrum is transformed into the wave number spectrum of the ocean wave through an empirical modulation transfer function, and then the cycle, wavelength and wave number are determined according to the peak position of the spectrum and the ocean wave theory Wave direction. Since the navigation X-band radar image has not been calibrated, the gray value of the radar image cannot directly reflect the height of the sea surface, and the wave height of the ocean wave must be determined by its empirical relationship with the signal-to-noise ratio of the radar image spectrum. The disadvantage of this method is that it is based on the assumption of spatial uniformity and temporal stability of the wave field, which rarely exists in real sea areas, especially near-shore areas. In the coastal sea area, with the shallower water depth and the reflection and refraction of the coast on waves, the wave field is generally inhomogeneous, resulting in low accuracy of the wave spectrum method. In addition, in low sea conditions, the radar echo reflected by the sea surface is weak, and the noise in the radar image will have a great impact on the wave spectrum, which will also cause the wave spectrum method to be inaccurate. Therefore, it is a technical problem to be solved in this field to invent an easy method capable of inverting sea wave parameters under different sea conditions, in uniform wave field and inhomogeneous wave field.

Contents of the invention

In order to solve the existing technical problems, the purpose of the present invention is to provide a kind of algorithm that can use the navigation X-band radar image sequence to invert the wave parameters of the uniform wave field and the non-uniform wave field under different sea conditions. For this reason, the present invention provides a Inversion Algorithm of Ocean Wave Parameters for Navigation X-band Radar Based on EOF Decomposition.

The technical solution adopted in the present invention is: a navigation X-band radar wave parameter inversion algorithm based on EOF decomposition, comprising the following steps:

First, EOF decomposition is performed on the navigation X-band radar image sequence of the wave field to obtain different modes of the wave field; then the maximum entropy power spectrum of the principal component of the first mode is obtained by using the Burg algorithm, according to the frequency corresponding to the peak value of the maximum entropy power spectrum Obtain the period of the ocean wave, and then use the dispersion relationship to obtain the wavelength of the ocean wave;

Using the linear relationship between the standard deviation of the principal component of a mode and the effective wave height to obtain the effective wave height of the ocean wave; using the space function and the principal component of the first mode to reconstruct the radar image sequence of the first mode of the wave field, the sequence Perform two-dimensional Fourier transform on any one of the images to obtain the wave number spectrum, and determine the direction of the quasi-wave according to the peak value of the wave number spectrum; then use the similarity of the wave stripes in two adjacent radar images to determine the direction of the sea wave.

The significant wave height obtained by using the linear relationship between the standard deviation of the principal component of a mode and the significant wave height is obtained by the following formula: SWH=A+B·std(z _i )

Among them, A and B are coefficients, and z _i represents the principal component of the i-th mode of EOF decomposition.

The determining the direction of the waves by using the similarity of the wave stripes in two adjacent radar images comprises the following steps:

Select two adjacent images I ₁ and I ₂ from the original radar image sequence; select a sub-image A in the center of the research area of image I ₁ , and divide the research area of image I ₂ into multiple sub-images with the same size as A Image, select the sub-image B of I ₂ that is the largest in the correlation coefficient between the sub-image A of I ₁ and all sub-images of I ₂ , the direction from the center of sub-image A to the center of sub-image B is the quasi-wave direction; Among the wave directions obtained from the peak value of the wave number spectrum, the direction closest to the quasi-wave direction is the wave direction.

The present invention has the following beneficial effects and advantages:

1. The present invention uses EOF to decompose the wave field into different modes, and extracts the wave height, cycle, wavelength and wave direction information of the waves from the main modes, effectively solving the inhomogeneity of the wave field and the large noise band in low sea conditions coming impact.

2. The maximum entropy power spectrum used in the present invention has the advantages of high resolution and is suitable for short time series, and the established relationship between the significant wave height and the principal component also has the advantages of being simple and easy to implement and having small errors.

Description of drawings

Fig. 1 is the algorithm flow chart of the present invention.

Detailed ways

The present invention will be further described in detail below in conjunction with the examples.

The present invention inverts the effective wave height, period, wavelength and wave direction of the sea wave from the navigation X-band radar image sequence. The specific steps are: firstly, the empirical orthogonal function (EOF) is used to decompose the navigation X-band radar image sequence to obtain the wave field different modalities. Use the Burg algorithm to calculate the maximum entropy power spectrum of the principal component of the first mode. The frequency corresponding to the peak of the spectrum is the peak frequency of the wave, and the reciprocal of the peak frequency is the peak period of the wave; use the standard deviation of the principal component and the linearity of the effective wave height relationship to obtain the effective wave height of the ocean wave; use the space function of the first mode and the principal component to reconstruct the wave field of the first mode, perform two-dimensional Fourier transform on the wave field to obtain the wave number spectrum, determine the wave direction according to the peak value of the spectrum, and then The 180° ambiguity of wave direction is eliminated by using the similarity of wave stripes in two adjacent radar images. The invention utilizes EOF to decompose the navigation X-band radar image sequence into different modalities, and extracts sea wave parameters from the principal components, thereby effectively eliminating the influence of the inhomogeneity of the wave field and the noise in the radar image on the inversion result.

Propose a kind of navigation X-band radar wave parameter inversion algorithm based on EOF decomposition in the present invention, concrete steps are as follows:

1. Select a research area from the navigation X-band radar image, generally select the area with obvious wave stripes, the size of the area can include 30° in azimuth and 256 pixels in radial direction. The EOF decomposition of the radar image sequence in the study area is used to obtain the different modes of the wave field, that is, the different spatial forms of the wave field and their corresponding principal components.

2. Use the Burg algorithm to calculate the maximum entropy power spectrum of the first principal component, and select the spectrum with a frequency within a certain range as the frequency spectrum of the ocean wave, where the frequency range refers to the frequency range of the ocean wave in general, such as 0.05Hz ~0.2Hz, the upper limit of the frequency interval should be less than the Nyquist frequency of radar sampling. The frequency corresponding to the peak of the frequency spectrum is the peak frequency f _p of the ocean wave, and the reciprocal of the peak frequency is the peak period T _p of the ocean wave; then the wavelength L is obtained according to the dispersion relationship of the wave:

ω ² =gktanhkd

in, is the angular frequency, is the wave number, g is the gravitational acceleration, and d is the water depth of the studied sea area.

3. Select any principal component of the first 20 modes, calculate its standard deviation, and determine the significant wave height (SWH) according to the linear relationship between the standard deviation and the effective wave height of the ocean wave:

SWH＝A+B·std(z _i )

Among them, A and B are undetermined coefficients, which are generally determined by comparing with the measured wave heights of on-site buoys; std(zi ₎ represents the standard deviation function, and z _i represents the i-th principal component of EOF decomposition, and each group of data contains 32 Generally, one of the 2nd to 15th principal components can be selected for the radar image sequence of the first image.

4. Using the space function and principal components of the first mode decomposed by EOF to reconstruct the wave field of the first mode, that is, to obtain a radar image sequence containing only the first mode. Select any one of the images, and perform two-dimensional Fourier transform on it to obtain the wavenumber spectrum S(k _x , _ky ) of the image, and determine the wave direction θ according to the peak position of the spectrum:

$\mathrm{<span\; class="notranslate">\; \&theta;</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; arctan</span>}\frac{{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; the\; y</span>}\mathrm{<span\; class="notranslate">\; 0</span>}}}{{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}\mathrm{<span\; class="notranslate">\; 0</span>}}}$

Wherein, (k _x0 , k _y0 ) is the position of the peak of the spectrum. Since this wavenumber spectrum contains two peaks, the wave direction at this time has a 180° directional ambiguity.

5. In order to eliminate direction ambiguity, select any two adjacent images from the original radar image sequence, and denote them as image I ₁ and image I ₂ respectively. Select a sub-image A in the center of the research area of image I ₁ , and divide the research area of image I ₂ into different sub-images B _ij of the same size as sub-image A (i, j represent the position of the sub-image in the research area, specifically The value is determined by the size of the study area and the size of the subimage). Calculate the correlation coefficient R _ij between sub-image A and sub-image B _ij , select the sub-image with the largest correlation coefficient, the center of which is the direction in which the wave propagates from the center of I ₁ to I ₂ , the wave direction obtained in step 4 is in the middle, and The closest thing to this direction is the direction of the waves, thus removing the 180° ambiguity of the wave direction from step 4.

The sub-image A selected in this step should generally contain one or several complete waveforms, and its area should not be too large or too small. If the area of the sub-image is too large, it may not be possible to find its position after the movement in the research area of image _I2 , and if the sub-image is too small, it cannot contain the information that can effectively identify the wave movement.

So far, the period, wavelength, effective wave height and wave direction of the ocean wave can be obtained through the above steps.

Claims (3)

1. The navigation X-band radar sea wave parameter inversion algorithm based on EOF decomposition is characterized by comprising the following steps of:

firstly, EOF decomposition is carried out on a navigation X-band radar image sequence of a sea wave field to obtain different modes of the sea wave field; then, obtaining a maximum entropy power spectrum of the first modal principal component by using a Burg algorithm, obtaining the period of the sea wave according to the frequency corresponding to the peak value of the maximum entropy power spectrum, and obtaining the wavelength of the sea wave by using a frequency dispersion relation;

obtaining the effective wave height of the sea wave by utilizing the linear relation between the standard deviation of a modal principal component and the effective wave height; reconstructing a radar image sequence of the first mode of the sea wave field by using a space function and a principal component of the first mode, performing two-dimensional Fourier transform on any image in the sequence to obtain a wave number spectrum, and determining a pseudo-wave direction according to a peak value of the wave number spectrum; and determining the direction of the sea waves by utilizing the similarity of the wave stripes in the two adjacent radar images.

2. An EOF decomposition-based navigation X-band radar sea wave parameter inversion algorithm as claimed in claim 1, wherein: the effective wave height of the sea wave obtained by utilizing the linear relation between the standard deviation of the main component of one mode and the effective wave height is obtained by the following formula: SWH ═ A + B · std (z)_i)

Wherein A, B is the coefficient, z_iRepresenting the principal component of the ith modality of the EOF decomposition.

3. An EOF decomposition-based navigation X-band radar sea wave parameter inversion algorithm as claimed in claim 1, wherein: the method for determining the direction of the sea waves by utilizing the similarity of the wave stripes in two adjacent radar images comprises the following steps:

two adjacent images I are selected from the original radar image sequence₁And I₂(ii) a In picture I₁Selecting a sub-image A from the center of the study area, and taking the image I₂Is divided into a plurality of sub-images of the same size as A, and I is selected₁Sub-images A and I of₂I being the largest of the correlation coefficients between all sub-images₂The direction from the center of the sub-image A to the center of the sub-image B is the pseudo-wave direction; among wave directions obtained from peaks of the wave number spectrum, a direction closest to the pseudo-wave direction is the wave direction.