CN115629364B - Satellite-borne small-angle SAR sea condition deviation simulation method for dynamic sea surface - Google Patents
Satellite-borne small-angle SAR sea condition deviation simulation method for dynamic sea surface Download PDFInfo
- Publication number
- CN115629364B CN115629364B CN202211651477.7A CN202211651477A CN115629364B CN 115629364 B CN115629364 B CN 115629364B CN 202211651477 A CN202211651477 A CN 202211651477A CN 115629364 B CN115629364 B CN 115629364B
- Authority
- CN
- China
- Prior art keywords
- sea surface
- satellite
- sea
- calculating
- distance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/40—Means for monitoring or calibrating
- G01S7/4052—Means for monitoring or calibrating by simulation of echoes
-
- 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
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/882—Radar or analogous systems specially adapted for specific applications for altimeters
-
- 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
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9021—SAR image post-processing techniques
- G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention provides a satellite-borne small-angle SAR sea condition deviation simulation method for a dynamic sea surface, and belongs to the technical field of marine observation. The method is used for constructing a sea surface scene based on satellite-borne parameters to complete the simulation of the dynamic sea surface; in the echo calculation, the sea surface is updated at any time according to the time of echo acquisition, and the echo superposition is carried out according to the mechanism of various modulation effects; the RD algorithm and the SRC algorithm are combined for use, the low-order coupling of the distance direction and the azimuth direction during squint when the incident angle is larger than 3 degrees is considered, the secondary distance compression and the distance compression are completed together, the distance direction focusing quality is improved, and the imaging precision and quality are improved; and (4) organizing an SSB lookup table, and supplementing the SSB lookup table of the traditional radar altimeter. The sea state deviation simulation method provided by the invention has higher accuracy and is convenient to search.
Description
Technical Field
The invention belongs to the technical field of marine observation, and particularly relates to a satellite-borne small-angle SAR sea condition deviation simulation method for a dynamic sea surface.
Background
Since 1970, synthetic Aperture Radars (SAR) have been applied to Sea Surface measurement and can acquire Sea Surface information such as Sea Surface Height (SSH), effective Wave Height (SWH), backscattering coefficient, and the like. In recent years, interferometric synthetic aperture radars measure sea surface information by obtaining phase difference information of main and auxiliary images by using results of a plurality of coherent SAR, and by means of observation modes of all-day time, all-weather, high spatial resolution and wide swath and the advantage that the data acquisition is not influenced by weather, compared with data acquired by a traditional altimeter, insar data can acquire marine data such as a marine digital elevation model and a sea surface flow field, and becomes one of main sources of future marine data.
However, the construction period of the satellite-borne SAR system is long, the manpower and material resources are expensive, and the sea surface information such as SSH and the like which is actually measured simultaneously comprises large error items, so that the sea surface measurement result difference caused by the influence of a single error item is difficult to accurately analyze, and therefore, SAR imaging sea surface simulation has certain necessity for measuring the influence of each error item of the satellite-borne SAR on the sea surface measurement, analyzing the difference of imaging results under different frequency bands and increasing an ocean information comparison data pool. The observation swath of an Interferometric imaging Altimeter (IRA) can reach hundreds of kilometers, the sea surface can be observed based on a small incident angle, sea surface data under higher space-time resolution can be obtained by virtue of the characteristics of high sampling rate and high precision, and research on the mesoscale and sub-mesoscale phenomena on the sea surface is facilitated. However, satellites of the imaging altimeter are rare at home and abroad, so that the simulation data of the imaging altimeter cannot be lost compared with the simulation data of the ocean altimeter in a large range.
With the increase of the amount of Sea surface information available and the deepening of human cognition on the Sea, the orbit error in the Sea surface height measurement process is greatly weakened by the mature precise orbit determination technology, and the Sea State deviation (SSB) becomes the first error source influencing the Sea surface height. The main part of the SSB is electromagnetic deviation, which is a height deviation introduced by the existence of wave crests and wave troughs and the sea surface electromagnetic scattering effect, the wave troughs can be used as better radar reflectors compared with the wave crests, and the backscattering power in unit area is larger than that of the wave crests, so that the sea level measured by the radar altimeter is lower than the real sea level, and the correction of the sea state deviation of the radar altimeter mainly depends on an empirical model, such as: parametric model estimation-linear regression using sea surface height SSH without Sea State Bias (SSB) correction determines SSB's relationship to variables such as wind speed (U) and effective wave height (SWH), and non-parametric model estimation. For the traditional radar altimeter, at present, researchers have constructed an SSB lookup table under different sea conditions with SWH and wind speed U as lookup ranges, and SSB measurement under an imaging altimeter system is yet to be further studied.
The value of the SSB is influenced by sea conditions, most of the existing simulation systems related to SAR imaging add error terms into the simulation system through empirical models, which is different from the actual imaging process, and each error term has a certain coupling, which cannot be considered singly, for example: because the satellite faces a continuous and uninterrupted moving sea surface generated by three different modulation actions of tilt modulation, velocity bunching and dynamic modulation when acquiring echo signals, and the data acquired by the image is a static comprehensive result obtained after simultaneously receiving various modulation actions in a data acquisition time period, the error in the single static sea surface subentry addition process in the initial state deviates from the actual echo acquisition imaging condition; in the simulation process, the simulation resolution and the scene size of the sea surface scene are mostly preset, and in the actual satellite-borne system, the scene size and the imaging resolution of the illuminated sea surface are acquired by the incidence angle and the load preset information.
Disclosure of Invention
The invention aims to provide a satellite-borne small-angle SAR sea condition deviation simulation method for a dynamic sea surface so as to make up for the defects of the prior art.
The traditional SAR simulation system carries out simulation based on a large incidence angle range, and because the rough sea surface scatterer mainly takes Bragg scattering under the large incidence angle, the Bragg scattering has small occupation ratio under the incidence angle smaller than 20 degrees, and the sea surface scattering mainly takes specular scattering as the main factor. The invention expands the wave spectrum from one dimension to two dimensions by using a double-scale model, is more effective for calculating a scattering field by using a geometric optical model under the condition of mirror scattering with small incident angles, is determined by the incident angle of a satellite carried by a satellite and the measuring time period of the satellite, and is simulated by a mode of acquiring a remote sensing image from an actual satellite. For the processing of sea surface echoes, the sea surface is updated in real time by adopting the slant distance corresponding to a sea surface scene, the time of a synthetic aperture and the simulated sea surface height obtained by simulation, so that the original echoes including velocity bunching modulation, inclination modulation and hydromechanics modulation are dynamically and directly obtained.
In the process of satellite height measurement, SSB becomes one of non-negligible errors, a lookup table created by data measured by a traditional radar altimeter can obtain an SSB value under an empirical condition under the condition that the effective wave height SWH and the wind speed U are known, and the SSB value is used for inversion and simulation of other sea surface information.
In order to achieve the technical purpose, the invention adopts the following specific technical scheme:
a satellite-borne small-angle SAR sea condition deviation simulation method for a dynamic sea surface comprises the following steps:
s1: establishing a simulation sea surface: setting satellite parameters, calculating the size of a sea surface scene, determining the resolution of the sea surface scene, establishing a scene grid, calculating a sea wave spectrum according to a linear filtering method to obtain an initial sea surface, namely a static sea surface at the time of t =0, and simultaneously obtaining a sea surface phase and a sea surface height;
s2: the dynamic sea surface simulation is realized by recalculating the sea surface phase and the sea surface height through updating the time variable at the static sea surface at the time of t = 0;
s3: updating the scattered field according to sea surface information:
s4: calculating to obtain simulation echo information;
s5: processing the simulated echo information based on a range-Doppler (RD) algorithm and a quadratic range compression (SRC) algorithm, and imaging under a small oblique angle by applying the RD algorithm and an improved SRC algorithm under the condition of an incident angle of 2-4 degrees according to the incident angle condition to obtain echo imaging images of the main antenna and the auxiliary antenna;
s6: the difference of the focused SLC1 information and the focused SLC2 information is caused by the different distances of the main antenna and the auxiliary antenna to the irradiation target point, the imaging image is registered by using a coherence coefficient method, and an interference pattern is obtained by complex conjugate multiplication;
s7: carrying out land removing and denoising treatment on the interference pattern;
s8: in the actual interference processing, only the main value (winding phase) of the interference phase can be obtained due to the trigonometric operation, but the real interference phase cannot be obtained, and then the Goldstein pruning method is adopted to perform phase unwrapping;
s9: elevation reconstruction: calculating SSH by using the unwrapped interference phase diagram to obtain sea surface height fluctuation;
s10: repeating the steps from S2 to S9 to obtain static SSH at the initial moment under the same sea surface state, and calculating to obtain SSB corresponding to the target point by using the obtained two sea surface heights SSH;
s11: and repeating the steps from S2 to S10, simulating the SSB values of the same satellite parameters under different sea surface states to obtain multiple experimental data, and constructing a satellite multidimensional database to complete dynamic sea surface simulation.
Further, in S1, the satellite parameters include: satellite carrier frequencyf 0 Pulse width T r And bandwidthB r Angle of incidenceθSatellite platform altitudealtAzimuth antenna lengthDAnd base lengthBBase line inclination angleαSampling ratef s And pulse repetition frequencyPRFSpeed of operation of the satellitevEtc.; calculating the near-ground distance and the far-ground distance of the satellite main and auxiliary antennas according to the space geometric relationship, and calculating the number of slope sampling according to the sampling rate on the slope, thereby obtaining the sea surface distance simulation scene resolution by using the beam width of the incident angle and the size of the incident angle, and obtaining the azimuth sampling interval according to the space geometric relationshipPRFCalculating the number of sampling points N y Self-simulation and calculation of sea surface azimuth simulation scene resolution
，N x And N y Taking a positive even number, uniformly multiplying by a number less than 1 in order to achieve a predetermined resolutionkA value to enhance the fineness of a scene, the scene size established as @>
，/>
。
Further, the S3 specifically is: the sea surface information is: calculating the mean square slope and the local incidence angle of the corresponding sea surface distance direction and azimuth direction according to the obtained sea surface phase, calculating Fresnel reflection coefficients under different polarization modes and different local incidence angles, obtaining Fresnel coefficients, the mean square slope, the local incidence angles and relative wind directions, and calculating and updating the scattering field according to the sea surface information based on a geometric optical model.
Further, S4 specifically is: simulating the real process of receiving the echo by the main antenna and the auxiliary antenna by using an original signal level simulation time domain method, calculating all echo signals reflected by the target by using a superposition method, and performing superposition calculation of scattered field echo on the sea surface updated in the steps 2) and 3 by using the calculated maximum synthetic aperture time of the target point, the distance between the target point and the satellite and the echo duration, and recording the echo within the receiving time, otherwise, not recording; because the sea surface is continuously updated, the theoretical distance between the target point and the satellite is changed at any moment, and the speed bunching, overlapping and fluid mechanics modulation information generated by the sea surface motion is added into the simulation echo at one time.
Further, in S5, the improved SRC is modified from SRC by the following steps:
(1) Performing distance compression to obtain a frequency spectrum after the distance compression, and performing Fourier transform to obtain a time domain spectrum;
(2) The azimuth spectrum of the system transfer function is represented as the convolution of two sub-spectrums, and only the stationary phase point is obtained to replace a quadratic term in the sinc function and a corresponding variable in an antenna directional diagram;
(3) And performing secondary distance compression in the azimuth direction by utilizing a third-order approximation distance model, the property of Fourier transform and the like, and then performing frequency domain range migration correction.
Further, S8 specifically is:
s8-1: determining the position of a residual error point in the obtained phase diagram, defining a residual error point judgment window with a fixed size, clockwise calculating the difference value of adjacent phases around the window, and adding or subtracting 2 pi to the value to return to a normal monotonous interval when the difference value exceeds the pi interval;
s8-2: calculating a residual error point, recording the residual error point when the sum of the four difference values in the S8-1 is not 0, and setting the value of the residual error point as +/-1 according to the positive and negative conditions of the residual error point and the 2 pi multiple;
s8-3: traversing residual points by using a search window, forming branch tangents by the residual points in the window, and establishing the branch tangents in the whole image until the residual points of the whole image are connected;
s8-4: and (4) unwinding the non-branch tangent line from the point to the periphery, changing the path when the non-branch tangent line touches the point on the branch tangent line until the whole graph is traversed, and unwinding the point if the unwound point exists around the point on the branch tangent line, otherwise marking the point as an abnormal point.
Further, S7 specifically is: calculating theoretical flat interference phase by using known ideal slope distance and target point incidence angleφ flat Obtaining the interference phase after removing the flat groundφ h (ii) a Because various noises exist in the interference phase, the interference pattern needs to be processed by a sine and cosine mean filtering method to achieve the purpose of removing the noises.
Further, in S10, sea surface parameters such as SWH, swell wavelength, wind speed, swell direction, and the like in one experiment are recorded at the same time.
Furthermore, the multidimensional database of S11 is used for analyzing data, is suitable for analyzing and organizing sea surface SSB values under different conditions, and can be obtained by searching the multidimensional database under the multidimensional screening condition when facing the sea surfaces under different states.
The invention has the following advantages and beneficial effects:
the method disclosed by the invention is used for constructing the sea surface scene based on the satellite-borne parameters to complete the simulation of the dynamic sea surface, and is more in line with the actual observation process. In the echo calculation, the sea surface is updated at any time according to the time of echo acquisition, echo superposition is carried out based on the mechanism of various modulation effects, and in the calculation process, the size of the echo is directly adjusted by the corresponding slope distance of each point of the sea surface, thereby avoiding the subentry superposition of various effects and achieving the purpose of simultaneously adding various sea surface modulation effects. The RD algorithm and the SRC algorithm are combined for use, the low-order coupling of the distance direction and the azimuth direction during squint when the incident angle is larger than 3 degrees is considered, the secondary distance compression and the distance compression are completed together, the distance focusing quality is improved, and the imaging precision and quality are improved. The SSB lookup table of the traditional radar altimeter is supplemented, the multi-dimensional imaging altimeter SSB lookup table is provided in the sea state deviation correction field, and a new thought is provided for further research of the sea state deviation.
The invention carries out the simulation of the small-angle InSAR interferogram based on the dynamic sea surface so as to make up the defects of full-link satellite-borne interference imaging simulation data and the supplement of an SSB lookup table under an IRA observation system under the current small-angle condition, and provides a sea condition deviation simulation method which has higher accuracy and is convenient to search. The imaging simulation platform of the imaging altimeter can be developed based on the invention, reference significance is provided for correction of satellite related errors of the existing imaging altimeter and the imaging altimeter which is not transmitted, and certain engineering significance is achieved.
Drawings
Fig. 1 is a flow chart of a satellite-borne small-angle SAR sea state deviation simulation method for a dynamic sea surface.
Fig. 2 shows the results of simulation experiments performed on the sea surface and corresponding scatterometry fields in an embodiment of the present invention.
Fig. 3 is a satellite-borne satellite acquisition point trajectory defined in the embodiment of the present invention.
Fig. 4 is a comparison chart of the display and registration of the L1A level product of the static sea surface in the embodiment of the present invention.
FIG. 5 is an ideal flattening result for dynamic sea surfaces and L1B product display in an embodiment of the present invention.
Fig. 6 is an interference result graph of a static sea surface and an interference result graph facing a dynamic sea surface in the embodiment of the invention.
FIG. 7 is a graph of the column-wise averaged results of SSB results in an example of the present invention.
Fig. 8 is a diagram illustrating an organization structure of a multidimensional database proposed in the present invention.
Detailed Description
The invention is further explained and illustrated below with reference to examples.
Example 1:
a satellite-borne small-angle SAR sea state deviation simulation method facing a dynamic sea surface is shown in figure 1 and comprises the following steps:
a satellite-borne small-angle SAR sea state deviation simulation method facing a dynamic sea surface is shown in figure 1 and comprises the following steps:
in this example, the satellite carrier frequency
Pulse width and bandwidth->
Angle of incidence->
Satellite platform height->
Azimuth antenna length->
And a base length->
Base line inclination->
Sampling rate->
And pulse repetition frequency
And the like.
(1) Determining relevant parameters of the simulated satellite, establishing a sea surface scene grid, and establishing the scene size as
，
。
Calculating the maximum synthetic aperture length due to the presence of the synthetic aperture lengthD max Echo in azimuth directiont a Collecting time and distance directionst r Acquisition time and corresponding sampling point theoretical slope distance of each pixel positiony r Theoretical flat ground distancey h And a certain margin is set to ensure complete information acquisition, and fig. 3 is a point acquisition track of a main antenna and an auxiliary antenna of the simulation satellite.
(2) And (4) performing rough sea surface dynamic simulation and generating a corresponding scattering field of the sea surface.
The sea surface is regarded as superposition of different subharmonics, a PM spectrum method is used for generating a wind wave spectrum and a surge spectrum, a linear filtering method is used for generating two groups of independent random numbers by using a Gaussian random number matrix to form a complex random number, the expansion coefficients of the wind wave spectrum and the surge spectrum are respectively calculated and coupled through fast Fourier transform, the height fluctuation of a rough sea surface space is obtained through fast Fourier transform, and the wind wave surge coupling coefficient, the surge phase and the sea surface fluctuation of a Monte Carlo method (Monte Carlo) which a static sea surface passes through are obtained. And (4) recalculating the surge phase and the sea surface height by updating the time variable to realize dynamic sea surface simulation. The PM spectrum method is expressed as:
wherein the content of the first and second substances,
beta is a dimensionless empirical constant, is->
Is defined as->
Beta is defined as 0.74, acceleration of gravity
And omega is the spatial frequency of the sea wave,U 19.5 for the wind speed at the sea surface height of 19.5m, in this example, as shown in fig. 2 (a), the wind direction angle is set to 45 °, the wind speed is set to 10m/s, the direction angle of the propagation of the swell is set to 45 °, the swell wavelength is set to 200m, and the effective wave height is set to 1m, so that the input wave spectrum is generated.
(3) The three-dimensional imaging altimeter generally adopts Ku-Ka wave band microwaves with relatively short wavelengths, and electromagnetic waves in the Ku wave band have the following characteristics under the condition that the incident angle does not exceed 10 degrees:
updating the sea surface in the step (2) according to the echo time information obtained in the step (1), synchronously updating the scattered field according to the sea surface phase information obtained in the step (2), wherein the scattered field corresponding to the sea surface at the initial moment is shown in a figure 2 (b) and is represented as follows:
wherein phi is an included angle between the wind direction and the azimuth direction,mss x and mss y respectively representing the slopes of the elements of the sea surface along the distance direction and the azimuth direction, and R represents the Fresnel coefficient.
(4) And respectively calculating the main antenna and the auxiliary antenna to obtain main echo and auxiliary echo.
And (2) calculating the maximum synthetic aperture length, azimuth sampling point time and sampling point number according to the scene size and the antenna length D, obtaining the distance sampling time and the sampling point number according to the near-ground distance and the far-ground distance obtained in the step (1) and the maximum synthetic aperture length, and adding allowance to the azimuth echo and the distance echo to ensure complete information receiving.
The echo intensity of each pixel point is expressed as:
wherein the content of the first and second substances,A 0 representing any complex constant, in this example 1, τ being the fast time of the distance direction, η being the slow time of the azimuth direction, R (η) representing the instantaneous slope distance, η c For the beam center offset time (the positive side is considered to be 0),ω a for azimuthal signal envelope, K r For adjusting the frequency.
(5) When the incidence angle is larger than 3 degrees, the imaging quality of the RD algorithm is influenced, the improved SRC algorithm is used for imaging under a small oblique angle, the coupling relation between the distance direction and the azimuth direction is considered, a third-order approximation distance model is introduced during processing to obtain a compression factor of Doppler frequency modulation, distance direction compression and secondary distance compression are completed simultaneously, and distance interpolation migration correction (RCMC) and azimuth direction processing are further performed.
Distance matching filterH r * Comprises the following steps:
wherein the content of the first and second substances,B r for the transmission signal bandwidth,KIs a frequency modulation slope,f τ Instantaneous doppler frequency.
R(t,R 0 ) A high-order approximation distance model represented by Doppler parameters, lambda is the wavelength of the transmitted electromagnetic wave, t is the time of the slow time domain,f DC representing the Doppler parameter, R, derived from the Doppler centroid 0 Denotes the distance from the radar to the target at t =0, t c Is composed of
Corresponding to the time of the closest distance of the radar to the target,vrepresenting the flying speed of the platform, c is the speed of light, and is taken>
：
The time domain spectrum is represented as:
f a for azimuthal doppler frequencies, the system transfer function can be expressed as:
(6) The SLC data obtained by the two antennas have a certain offset, for example, fig. 4 (a) and 4 (b) are SLC1 and SLC2 obtained by calculating echo information of the main and auxiliary antennas through the RD algorithm, respectively, then the images need to be registered by using a coherence coefficient method, the coherence coefficient of the main and auxiliary images in the matching window mxm and the searching window nxn is calculated, the maximum correlation coefficient is calculated to determine the registration offset, and coarse registration is performed.
And &>
For the amplitude of the two single-view complex images,uandvas offset, maximum correlation coefficientRExpressed as:
interpolating to 0.01 pixel on the basis of the rough registration coordinate, repeating the above process, and performing fine registration to make the registration of the primary and secondary antennas achieve higher precision, performing complex conjugate multiplication on the primary and secondary images to obtain an interference pattern, where fig. 4 (c) is a complex conjugate result of an unregistered primary and secondary image, where obvious rough noise is visible, and fig. 4 (d) is a complex conjugate result of an unregistered primary and secondary image, where the fringes are clear, and the complex conjugate calculation formula is as follows:
(7) The calculated theoretical flat interference phase is shown in fig. 5 (a), the interference phase after the flat is removed by subtraction is shown in fig. 5 (b), and the noise is removed by sine and cosine mean filtering and phase unwrapping. The theoretical flat interference phase is expressed as:
the phase after land leveling is calculated as:
where p is a constant related to the radar antenna operating mode, in this example, a self-transmitting and self-receiving mode, and p =2.
(8) Calculating the SSH to obtain a rough sea surface interference result, as shown in fig. 6, fig. 6 (a) is a calculation result of the interference sea surface height under the static sea surface condition, and fig. 6 (b) is an interference sea surface result obtained by updating the sea surface in a short time.
(9) Repeating the steps (2) to (8) under the same sea surface parameters (including SWH, wind speed U, swell wavelength, swell direction and the like) to obtain static stateh s And collecting the results of continuously updating the sea surface during the echo processh e And calculating to obtain the SSB corresponding to the target point by using the obtained twice sea level height SSH, and simultaneously recording the specific numerical value of the sea level parameter under one experiment.
SSB=h s -h e
The results of one experiment were averaged column by column to give a column average of SSB distributed along the distance direction as shown in fig. 7.
(10) And (5) replacing sea surface parameters, repeating the experiment step (9), simulating the SSB values of the same satellite parameters under different sea surfaces to obtain multiple times of experiment data, and constructing a database. The main parameters are organized in a cubic model: the x-axis is effective wave height, the y-axis is surge direction, the z-axis is surge wavelength, and the final storm two-dimensional lookup table is guided through the sequence index of the cube storage lookup table: the x-axis is wind speed and the y-axis is wind direction, and the corresponding SSB value is found in the table, as shown in fig. 8 (a).
If more parameters exist, the data size is too large, and the dimension needs to be increased, a three-dimensional search can be added to the original dimension once, as shown in fig. 8 (b), the position of a second-order three-dimensional space is obtained through a three-dimensional index label obtained by the one-time search, then the search is performed in the second-order three-dimensional space to obtain the index of a two-dimensional lookup table, and then a specific table is searched according to the index to obtain the final SSB value.
In summary, the present invention aims to provide a new lookup table type solution for calibrating sea state deviation of an imaging altimeter, which combines with an actual satellite-borne imaging mode, starts simulation from a sea scene which can be actually covered during pulse acquisition, then simulates echo generation of a dynamic scene under an existing static ideal sea scene, acquires echoes during sea motion, adds effects of velocity bunching, folding, hydrodynamic modulation, and the like at one time to obtain sea information containing SSB, compares the sea information with an ideal static sea, performs subtraction to obtain a specific SSB value, and searches and organizes the sea information by using a multi-dimensional database.
Claims (8)
1. A satellite-borne small-angle SAR sea condition deviation simulation method for a dynamic sea surface is characterized by comprising the following steps:
s1: establishing a simulation sea surface: setting satellite parameters, calculating the size of a sea surface scene, determining the resolution of the sea surface scene, establishing a scene grid, calculating a sea wave spectrum according to a linear filtering method to obtain an initial sea surface, namely a static sea surface at the time of t =0, and simultaneously obtaining a sea surface phase and a sea surface height;
s2: the dynamic sea surface simulation is realized by recalculating the sea surface phase and the sea surface height through updating the time variable at the static sea surface at the time of t = 0;
s3: updating the scattered field according to sea surface information:
s4: calculating to obtain simulation echo information;
s5: processing the simulated echo information based on a Range Doppler (RD) algorithm and a quadratic range compression (SRC) algorithm, and imaging under a small oblique angle by applying the RD algorithm and an improved SRC algorithm under the condition of an incident angle of 2-4 degrees according to the incident angle condition to obtain echo imaging images of the main antenna and the auxiliary antenna;
s6: the difference of the focused SLC1 information and the focused SLC2 information is caused by the different distances of the main antenna and the auxiliary antenna to the irradiation target point, the imaging image is registered by using a coherence coefficient method, and an interference pattern is obtained by complex conjugate multiplication;
s7: carrying out land removing and denoising treatment on the interference pattern;
s8: then performing phase unwrapping on the fiber by adopting a Goldstein branch cutting method;
s9: elevation reconstruction: calculating SSH by using the unwrapped interference phase diagram to obtain sea surface height fluctuation;
s10: repeating S2 to S9 to obtain static SSH at the initial moment under the same sea surface state, and calculating to obtain SSB of the corresponding target point by using the obtained two-time sea surface height SSH;
s11: and repeating the steps from S2 to S10, simulating the SSB values of the same satellite parameters under different sea surface states to obtain multiple experimental data, and constructing a satellite multidimensional database to complete dynamic sea surface simulation.
2. The satellite-borne small-angle SAR sea state deviation simulation method of claim 1, wherein in S1, the satellite parameters include: satellite carrier frequency f 0 Pulse width T r And bandwidth B r The incidence angle theta, the satellite platform height alt, the azimuth antenna length D, the base line length B, the base line inclination angle alpha and the sampling rate f s And pulse repetition frequency PRF, satellite operating speed v; calculating the near ground distance and the far ground distance of the satellite main and auxiliary antennas according to the space geometric relationship, and calculating the sampling number of the slant distance according to the sampling rate on the slant distance, thereby obtaining the sea surface distance direction simulation scene resolution by using the beam width of the incident angle and the size of the incident angle, calculating the sampling interval of the azimuth direction according to the PRF, and calculating the number of the sampling points N y Self-simulation, calculating sea surface azimuth simulation scene resolution delta y = kxv/PRF, N x And N y Taking a positive even number, in order to achieve the aim of uniformly multiplying the proposed resolution by a k value smaller than 1 to enhance the scene fineness, the scene size is established as (delta x N) x )，(Δy×N y )。
3. The satellite-borne small-angle SAR sea state deviation simulation method of claim 1, wherein the S3 specifically is: the sea surface information is: calculating the mean square slope and the local incidence angle of the corresponding sea surface distance direction and azimuth direction according to the obtained sea surface phase, calculating Fresnel reflection coefficients under different polarization modes and different local incidence angles, obtaining Fresnel coefficients, the mean square slope, the local incidence angles and relative wind directions, and calculating and updating the scattering field according to the sea surface information based on a geometric optical model.
4. The satellite-borne small-angle SAR sea state deviation simulation method of claim 1, wherein the S4 specifically is: simulating the real process of receiving echoes by the main antenna and the auxiliary antenna by using an original signal level simulation time domain method, calculating all echo signals reflected by the target by using a superposition method, performing superposition calculation of scattered field echoes on the sea surface updated each time by using the calculated maximum synthetic aperture time of the target point, the distance between the target point and the satellite and the echo duration, and recording the echoes within the receiving time, otherwise, not recording; because the sea surface is continuously updated, the theoretical distance between the target point position and the satellite is changed at any moment, and the velocity bunching, folding and fluid mechanics modulation information generated by the sea surface movement is added into the simulation echo at one time.
5. The method for simulating sea state deviation of spaceborne small-angle SAR as claimed in claim 1, wherein in S5, the improved SRC is improved on the basis of SRC as follows:
(1) Distance compression is carried out to obtain a frequency spectrum after distance compression, and a time domain spectrum is obtained through Fourier transform;
(2) The azimuth spectrum of the system transfer function is represented as the convolution of two sub-spectrums, and only the stationary phase point is obtained to replace a quadratic term in the sinc function and a corresponding variable in an antenna directional diagram;
(3) And performing secondary distance compression in the azimuth direction by using a third-order approximation distance model and the property of Fourier transform, and then performing frequency domain range migration correction.
6. The satellite-borne small-angle SAR sea state deviation simulation method of claim 1, wherein the S8 is specifically: s8-1: determining the position of a residual error point in the obtained phase diagram, defining a residual error point judgment window with a fixed size, clockwise calculating the difference value of adjacent phases around the window, and adding or subtracting 2 pi to the value to return to a normal monotonous interval when the difference value exceeds the pi interval;
s8-2: calculating a residual error point, recording the residual error point when the sum of the four difference values in the S8-1 is not 0, and setting the value of the residual error point as +/-1 according to the sum of the residual error point and the positive and negative conditions of multiplied by 2 pi number;
s8-3: traversing residual points by using a search window, forming branch tangents by the residual points in the window, and establishing the branch tangents in the whole image until the residual points of the whole image are connected;
s8-4: and (4) unwinding the non-branch tangent line from the point to the periphery, changing the path when the non-branch tangent line touches the point on the branch tangent line until the whole graph is traversed, and unwinding the point if the unwound point exists around the point on the branch tangent line, otherwise marking the point as an abnormal point.
7. The satellite-borne small-angle SAR sea state deviation simulation method of claim 1, wherein the S7 specifically is: calculating theoretical flat interference phase by using known ideal slope distance and target point incidence angle
Obtaining an interference phase after land leveling>
Because various noises exist in the interference phase, the interference pattern needs to be processed by a sine and cosine mean filtering method to achieve the purpose of removing the noises。
8. The satellite-borne small-angle SAR sea state deviation simulation method of claim 1, wherein sea surface parameters under one experiment are recorded simultaneously in S10: SWH, swell wavelength, wind speed, swell direction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211651477.7A CN115629364B (en) | 2022-12-22 | 2022-12-22 | Satellite-borne small-angle SAR sea condition deviation simulation method for dynamic sea surface |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211651477.7A CN115629364B (en) | 2022-12-22 | 2022-12-22 | Satellite-borne small-angle SAR sea condition deviation simulation method for dynamic sea surface |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115629364A CN115629364A (en) | 2023-01-20 |
| CN115629364B true CN115629364B (en) | 2023-03-28 |
Family
ID=84910023
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211651477.7A Active CN115629364B (en) | 2022-12-22 | 2022-12-22 | Satellite-borne small-angle SAR sea condition deviation simulation method for dynamic sea surface |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115629364B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1262792A1 (en) * | 2001-05-31 | 2002-12-04 | Starlab Barcelona SL | System for monitoring a feature of a surface by reflected satellite navigation signals |
| CN114594477A (en) * | 2022-03-18 | 2022-06-07 | 北京航空航天大学 | Echo domain-based satellite-borne SAR (synthetic Aperture Radar) marine target signal detection method and device |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000199790A (en) * | 1999-01-06 | 2000-07-18 | Mitsubishi Electric Corp | Composite aperture radar device and image reproducing method of the composite aperture radar device |
| US7486227B2 (en) * | 2005-08-23 | 2009-02-03 | The United States Of America As Represented By The Secretary Of The Navy | System and method for removal of sea-state bias in satellite altimetry data |
| CN103364766B (en) * | 2012-04-01 | 2015-02-04 | 中国科学院电子学研究所 | External calibration method of satellite-borne interferometric synthetic aperture radar (InSAR) system |
| CN105093188B (en) * | 2015-08-24 | 2017-05-24 | 中国科学院电子学研究所 | SAR ocean image sea wave clutter suppression method based on sub-aperture image |
| CN110988878B (en) * | 2019-11-28 | 2023-04-07 | 中国海洋大学 | SAR (synthetic Aperture Radar) sea wave imaging simulation method based on RD (RD) algorithm |
| CN113126122B (en) * | 2021-04-02 | 2023-03-28 | 青岛海洋科学与技术国家实验室发展中心 | Interference imaging altimeter and laser radar double-satellite accompanying marine observation method and system |
| CN113900069A (en) * | 2021-09-29 | 2022-01-07 | 中国科学院国家空间科学中心 | Vertical deviation calculation method and system based on interference imaging altimeter |
| CN114047511B (en) * | 2021-11-02 | 2022-04-12 | 中国海洋大学 | Time-varying sea surface airborne SAR imaging simulation method based on CSA algorithm |
| CN114415181B (en) * | 2022-03-31 | 2022-07-12 | 南方海洋科学与工程广东省实验室(广州) | Method and device for generating original echo of synthetic aperture radar |
-
2022
- 2022-12-22 CN CN202211651477.7A patent/CN115629364B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1262792A1 (en) * | 2001-05-31 | 2002-12-04 | Starlab Barcelona SL | System for monitoring a feature of a surface by reflected satellite navigation signals |
| CN114594477A (en) * | 2022-03-18 | 2022-06-07 | 北京航空航天大学 | Echo domain-based satellite-borne SAR (synthetic Aperture Radar) marine target signal detection method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115629364A (en) | 2023-01-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Brüning et al. | Monte-Carlo simulation studies of the nonlinear imaging of a two dimensional surface wave field by a synthetic aperture radar | |
| Hagberg et al. | Repeat-pass SAR interferometry over forested terrain | |
| Farhat et al. | Prospects for three‐dimensional projective and tomographic imaging radar networks | |
| CN102176017A (en) | Compound electromagnetic scattering value simulation method of electrically large complex object and rough surface background | |
| CN111006743A (en) | Method for eliminating interference in water level measurement based on plane radar water level gauge | |
| Fortuny | Efficient algorithms for three-dimensional near-field synthetic aperture radar imaging | |
| Yitayew et al. | Lake and fjord ice imaging using a multifrequency ground-based tomographic SAR system | |
| Ferro-Famil et al. | Synthetic aperture radar imaging | |
| Monakov et al. | Statistical properties of FMCW radar altimeter signals scattered from a rough cylindrical surface | |
| Knight et al. | Tomographic Techniques Applied to | |
| CN115629364B (en) | Satellite-borne small-angle SAR sea condition deviation simulation method for dynamic sea surface | |
| Pascazio et al. | Synthetic aperture radar imaging by one-bit coded signals | |
| Knaell | Three-dimensional SAR from practical apertures | |
| Dogan et al. | Time domain SAR raw data simulation of distributed targets | |
| Wang et al. | Sea surface imaging simulation for 3D interferometric imaging radar altimeter | |
| RU2327190C1 (en) | Method of obtaining three-dimensional radar image of rotating, pitching and banking object, with multi-frequency pulsed probing | |
| Lee | Forest parameter estimation using polarimetric SAR interferometry techniques at low frequencies | |
| Pepin et al. | Point source localization from de-ramped phase history bound on interferometric synthetic aperture radar (IFSAR) accuracy | |
| Delliere et al. | SAR measurement simulation on urban structures using a FDTD technique | |
| CN112764030B (en) | Sea surface SAR image clutter generation method based on electromagnetic and statistical hybrid model | |
| Detlefsen | Industrial applications of microwave imaging | |
| Kim et al. | Synthetic aperture imaging of dispersive targets | |
| Dong et al. | Spaceborne Interferometric Imaging Radar Altimeter Simulator for Measurement of Global Oceanic Topography | |
| Yang et al. | An improved two-scale method for simulating the backscattering of random rough surfaces | |
| Chiaradia et al. | COSMO/SKYMED AO projects-advanced 2D and 3D focusing of COSMO/SKYMED SAR data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |