CN104101864A - Navigation X-waveband radar ocean wave parameter inversion algorithm based on EOF decomposition - Google Patents
Navigation X-waveband radar ocean wave parameter inversion algorithm based on EOF decomposition Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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Abstract
The invention relates to a navigation X-waveband radar ocean wave parameter inversion algorithm based on EOF decomposition. The method comprises the following steps: first of all, carrying out EOF decomposition on a navigation X-waveband radar image sequence to obtain different modalities; then by use of a Burg algorithm, obtaining a maximum entropy power spectrum of the main component of a first modality, and according to a spectrum peak value, obtaining a period and a wavelength of ocean waves; by use of a linear relation between a standard deviation of the main component of a modality and an effective wave height, obtaining an effective wave height of the ocean waves; by use of a space function of the first modality and the main component of the first modality, reconstructing a radar image sequence of the first modality of an ocean wave field, performing two-dimensional Fourier transformation on any one image in the sequence, and according to an obtained wave-number spectrum peak value, determining a simulation wave direction; and by use of wave stripe similarities in two adjacent radar images, determining an ocean wave direction. According to the invention, by use of an EOF, the ocean wave field is decomposed into the different modalities, and the wave height, the period, the wavelength and the wave direction of the ocean waves are extracted from major modalities, such that the problem of influences caused by inhomogeneity of the wave field and large noise in case of a low ocean condition is solved.
Description
Technical Field
The invention belongs to the technical field of ocean remote sensing, and relates to an ocean wave parameter inversion algorithm of a navigation X-band radar based on EOF decomposition.
Background
Sea waves have important influence on the production and life of people, and the construction of ports and navigation channels near the shore, the production of fishery, the navigation of ships in the big ocean and the like are closely related to the sea waves. Therefore, the observation of sea waves has important practical significance. Conventional observation means such as buoys can accurately obtain the change information of the sea waves, but they can only obtain the change of the sea waves at a fixed point and are not easy to manage and maintain. The navigation X-band radar is an all-weather high-resolution imaging radar and can be used for extracting wave height, period, wavelength, wave direction and other information of sea waves from a sea clutter image.
The existing method for inverting the wave parameters from a navigation X-band radar image sequence is mainly based on a wave spectrum. The method comprises the steps of firstly carrying out three-dimensional Fourier transform on a radar image sequence to obtain a radar image spectrum, then converting the radar image spectrum into a wave number spectrum of sea waves through an empirical modulation transfer function, and then determining the period, the wavelength and the wave direction of the sea waves according to the peak position of the spectrum and the sea wave theory. Because the image of the navigation X-band radar is not calibrated, the gray value of the radar image cannot directly reflect the height of the sea surface, and the wave height of sea waves is determined by the empirical relationship between the wave height and 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 is rarely present in real sea areas, especially near shore areas. In the offshore area, the wave field is generally uneven along with the shallow depth of water and the reflection and refraction of the seashore to waves, so that the accuracy of the wave spectrum method is not high. In addition, in a low sea state, the radar echo reflected by the sea surface is weak, and noise in a radar image has a great influence on a sea wave spectrum, which also causes the sea wave spectrum method to be inaccurate. Therefore, the invention provides a feasible method capable of inverting the wave parameters in the uniform wave field and the non-uniform wave field under different sea conditions, which is a technical problem to be solved in the field.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention aims to provide an algorithm capable of utilizing a navigation X-band radar image sequence to invert wave parameters of a uniform wave field and a non-uniform wave field under different sea conditions, and therefore, the invention provides an EOF decomposition-based navigation X-band radar wave parameter inversion algorithm.
The technical scheme adopted by the invention is as follows: the navigation X-band radar sea wave parameter inversion algorithm based on EOF decomposition comprises the following steps:
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.
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, ziRepresenting the principal component of the ith modality of the EOF decomposition.
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.
The invention has the following beneficial effects and advantages:
1. according to the invention, the sea wave field is decomposed into different modes by using the EOF, and the wave height, period, wavelength and wave direction information of the sea waves are extracted from the main modes, so that the influence caused by non-uniformity of the wave field and large noise under low sea conditions is effectively solved.
2. The maximum entropy power spectrum used by the invention has the advantages of high resolution and suitability for short time sequences, and the established relation between the effective wave height and the main component also has the advantages of simplicity, easy realization and small error.
Drawings
FIG. 1 is a flow chart of the algorithm of the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples.
The method is used for inverting the effective wave height, the period, the wavelength and the wave direction of the sea wave from a navigation X-waveband radar image sequence, and comprises the following specific steps: firstly, an Empirical Orthogonal Function (EOF) decomposition is carried out on a navigation X-band radar image sequence to obtain different modes of a sea wave field. Calculating a maximum entropy power spectrum of a main component of a first mode by using a Burg algorithm, wherein the frequency corresponding to the peak value of the spectrum is the peak value frequency of the sea wave, and the reciprocal of the peak value frequency is the peak value period of the sea wave; obtaining the effective wave height of the sea waves by utilizing the linear relation between the standard deviation of the main components and the effective wave height; the wave field of the first mode is reconstructed by utilizing the space function and the principal component of the first mode, the wave number spectrum is obtained by performing two-dimensional Fourier transform on the wave field, the wave direction is determined according to the peak value of the spectrum, and the 180-degree ambiguity of the wave direction is eliminated by utilizing the similarity of wave stripes in two adjacent radar images. According to the method, the navigation X-band radar image sequence is decomposed into different modes by using the EOF, and the sea wave parameters are extracted from the main components, so that the influences of the nonuniformity of a wave field and the noise in the radar image on the inversion result are effectively eliminated.
The invention provides an EOF decomposition-based navigation X-band radar sea wave parameter inversion algorithm, which comprises the following specific steps of:
1. a research area is selected from a navigation X-band radar image, an area with obvious sea wave stripes is generally selected, and the size of the area can be that the azimuth direction comprises 30 degrees and the radial direction comprises 256 pixels. And performing EOF decomposition on the radar image sequence in the research area to obtain different modes of the sea wave field, namely different spatial forms of the sea wave field and corresponding main components of the sea wave field.
2. And calculating the maximum entropy power spectrum of the first main component by using a Burg algorithm, and selecting a spectrum with a frequency within a certain range as a frequency spectrum of the sea waves, wherein the frequency range refers to the frequency range of the sea waves in general, such as 0.05 Hz-0.2 Hz, and 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 of the sea wavepThe reciprocal of the peak frequency is the peak period T of the sea wavep(ii) a And then obtaining the wavelength L according to the dispersion relation of the waves:
ω2＝gktanhkd
wherein,in order to be the angular frequency of the frequency,wave number, g acceleration of gravity, d depth of water in the sea area under study.
3. Selecting any main component in the first 20 modes, calculating the standard deviation of the main component, and determining the effective wave height (SWH) according to the linear relation between the standard deviation and the effective wave height of the sea waves:
SWH＝A+B·std(zi)
wherein A, B is a waiting coefficient, generally determined by comparing with the measured wave height of the buoy on site; std (z)i) Denotes the standard deviation function, ziThe ith principal component representing the EOF decomposition may generally be one of the 2 nd to 15 th principal components for a radar image sequence containing 32 images per set of data.
4. And reconstructing the sea wave field of the first mode by utilizing the spatial function and the principal component of the first mode decomposed by the EOF, so as to obtain the radar image sequence only containing the first mode. Selecting any one of the images, and performing two-dimensional Fourier transform on the selected image to obtain a wave number spectrum S (k) of the imagex,ky) Determining the wave direction theta according to the peak position of the spectrum:
wherein (k)x0,ky0) Is where the peak of the spectrum is located. Since this wave number spectrum includes two peaks, the wave direction at this time is blurred in a direction of 180 °.
5. In order to eliminate directional blurring, two random adjacent images are selected from an original radar image sequence and are respectively marked as an image I1And image I2. In picture I1Selecting a sub-image A from the center of the study area, and taking the image I2Is divided into different sub-images B of the same size as sub-image aij(i, j denotes the position of the sub-image in the investigation region, the specific value being determined by the size of the investigation region and the size of the sub-image). Calculating sub-image A and sub-image BijCoefficient of correlation between RijSelecting the sub-image with the maximum correlation coefficient, wherein the center of the sub-image is the wave start I1Is propagated to I2The direction closest to this direction, among the wave directions obtained in step 4, is the direction of the sea waves, so that the 180 ° ambiguity of the wave direction in step 4 is eliminated.
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. The area of the sub-image may not be too large in image I2The position of the sub-image after the movement is found in the research area, and the sub-image cannot contain information which can effectively identify the movement of the wave when the sub-image is too small.
Therefore, the period, the wavelength, the effective wave height and the wave direction of the sea waves can be obtained through the 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, ziRepresenting 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.
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Cited By (15)
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| CN104977583A (en) * | 2015-07-08 | 2015-10-14 | 中国船舶重工集团公司第七一九研究所 | Method for X-band radar wave retrieval based on empirical orthogonal decomposition |
| CN106990402A (en) * | 2017-03-30 | 2017-07-28 | 南京信息工程大学 | A kind of navigation X-band radar wave group detection method based on Wave Theory |
| CN106990404A (en) * | 2017-03-30 | 2017-07-28 | 南京信息工程大学 | A kind of autoscale algorithm using X-band radar inverting sea wave height of navigating |
| CN107101619A (en) * | 2017-05-08 | 2017-08-29 | 中国海洋大学 | Wave wavelength measurement method based on the adjacent wave height data dependence in space |
| CN108551412A (en) * | 2018-05-03 | 2018-09-18 | 网宿科技股份有限公司 | Monitoring data noise reduction process method and apparatus |
| CN108717190A (en) * | 2018-05-24 | 2018-10-30 | 哈尔滨哈船导航技术有限公司 | Ocean wave measurement system |
| CN108957590A (en) * | 2018-05-22 | 2018-12-07 | 南京信息工程大学 | A kind of extracting method based on the real-time index of EEOF quasi-biweekly oscillation |
| CN109283495A (en) * | 2018-09-06 | 2019-01-29 | 南京信息工程大学 | A kind of X-band radar ocean current inversion method based on cross-spectral analysis |
| CN110068309A (en) * | 2019-03-28 | 2019-07-30 | 中国海洋大学 | One kind being based on New High Order disperse relationship deep water offshore measurement method and device |
| CN110361730A (en) * | 2019-07-18 | 2019-10-22 | 自然资源部第一海洋研究所 | A kind of boat-carrying boating type wave radar measurement system |
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| CN113514833A (en) * | 2021-04-25 | 2021-10-19 | 南京信息工程大学 | Sea surface arbitrary point wave direction inversion method based on sea wave image |
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| CN104977583A (en) * | 2015-07-08 | 2015-10-14 | 中国船舶重工集团公司第七一九研究所 | Method for X-band radar wave retrieval based on empirical orthogonal decomposition |
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| CN112862868A (en) * | 2021-01-31 | 2021-05-28 | 南京信息工程大学 | Motion sea wave image registration fusion method based on linear transformation and wavelet analysis |
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| CN113514833B (en) * | 2021-04-25 | 2023-10-27 | 南京信息工程大学 | Sea surface arbitrary point wave direction inversion method based on sea wave image |
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