CN105677942B - A kind of spaceborne natural scene SAR complex image data rapid simulation method of repeat track - Google Patents
A kind of spaceborne natural scene SAR complex image data rapid simulation method of repeat track Download PDFInfo
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Abstract
The invention discloses a kind of spaceborne natural scene SAR complex image data rapid simulation methods of repeat track, this method simulates SAR satellite transit track, ground scene is emulated according to satellite-borne SAR satellite imagery principle and SAR satellite haplopia complex pattern signal model, directly obtains several repeat tracks SAR complex image data.Zero doppler imaging position of satellite is iterated to calculate using a kind of fast method to obtain oblique distance information, backscattering coefficient is calculated using scattering model is simplified, proposes a kind of repeat track model of simplification to generate several any SAR complex image datas of controllable baseline length.The present invention overcomes the slow-footed disadvantages of conventional echo emulation mode, but also can handle for interference and provide prior information with aid in treatment or assessment processing result.
Description
Technical Field
The invention belongs to the technical field of Synthetic Aperture Radars (SAR), and relates to a rapid simulation method for SAR complex image data of a repetitive orbit satellite-borne natural scene.
Background
The synthetic aperture radar satellite is a high-resolution microwave remote sensing satellite for observing the earth based on space height, has wide application prospect in the fields of military affairs, ocean, agriculture, forestry and the like, has transmitted a plurality of SAR satellites in the countries of America, European Union, Canada, Japan and the like, has obtained great success, and generally adopts a digital simulation technology to realize the optimization design of the overall scheme of a satellite system in the process of developing the SAR satellites abroad. The satellite-borne SAR complex image simulation can provide image data with priori knowledge for SAR system error simulation analysis, radar image processing and interference SAR technology research, and has very important significance for engineering development research and application research of SAR systems. Interferometric Synthetic Aperture Radar (InSAR) refers to a new means for measuring surface elevation information, which is applied to the fields of military, geology, disaster monitoring and the like in many countries, and is used as a special application method of InSAR, and a differential Interferometric Synthetic Aperture Radar (DInSAR) technology is also widely regarded in various social circles at the beginning of the century. The ground surface deformation detection precision of the device can reach a centimeter level and even a millimeter level, and the stability and the development prospect of the device enable the device to gradually replace the traditional level detection method and the GPS method in the field of ground surface deformation monitoring and play a vital role more and more. For InSAR and D-InSAR technologies, a plurality of SAR complex image data generated by a certain baseline repeated satellite orbit (all orbit rising or all orbit falling) to the same target area are needed as data sources, wherein PS-DInSAR needs more than ten SAR complex image data, but for repeated orbits of certain scenes or imaging conditions, real satellite-borne SAR complex image data are lacked, and the current real data are also generally lacked of effective prior auxiliary data, so that the method is not beneficial to analysis and verification of an algorithm. Therefore, it is very important to perform computer digital simulation of the repetitive orbit spaceborne SAR complex image data aiming at the natural scene.
Julian establishes an SAR image simulation system for the first time according to the requirement of SAR image interpretation technology research, then Kaupp utilizes the system to research the influence of a radar incidence angle on the characteristics of a satellite-borne SAR image, primary attempts are made on the application of the simulation technology to SAR satellite system scheme design, and then the research of the SAR image simulation technology is promoted by the vigorous development of the SAR satellite technology. France schetti establishes an SARAS simulation system, and provides a three-dimensional ground scene SAR image simulation model. The SAR complex image data simulation is a technology for simulating and generating a radar image according to certain platform orbit parameters and radar parameters and a radar imaging mechanism according to certain ground terrain data, and the SAR complex image data simulation is mainly used for synthesizing the SAR complex image data by combining certain radar geometric relations.
The work of the simulation of the satellite-borne natural scene SAR complex image data mainly comprises three aspects, namely, the simulation of the spatial position, namely the determination of the spatial position relation between an SAR satellite imaging orbit and a ground natural scene; secondly, geometric feature simulation, namely establishing a mathematical positioning relation between ground points and image points, and simulating the characteristics of the SAR image such as overlap, perspective shrinkage, top-bottom inversion and the like; and thirdly, radiation characteristic simulation, namely simulating the characteristics of shadow, speckle noise and the like on the SAR image. According to different simulation methods, SAR simulation can be divided into original echo simulation and image simulation: the echo simulation is that echo data is obtained by simulating the backscattering coefficient of a ground object according to the working principle of an SAR system, and then an SAR image is obtained through an imaging processing algorithm; the image simulation is to directly simulate the SAR complex image data after imaging by taking the SAR system and the imaging processing as a linear system processing from the composition of the SAR image. The first method generally adopts a point-by-point iteration echo solving method when echo data are solved, the calculation amount is huge, and especially, the time consumption is overlarge when a plurality of images of a repeated track are calculated; the second method is simple in operation and can well meet the requirements of InSAR processing, so that the invention adopts the second method, namely, SAR complex image data is directly simulated without echo simulation.
Disclosure of Invention
The invention aims to provide a computer digital rapid simulation method of repeated orbit spaceborne SAR complex image data aiming at a natural scene, which can be used for large-scale scene simulation, can acquire simulated SAR complex image data of any number of repeated orbits (all orbit rising or all orbit falling) for different orbit parameters and SAR satellite parameters, and can be used in the fields of SAR system error simulation analysis, radar image processing, interference SAR technical research and the like.
The technical scheme adopted by the invention is as follows: a method for rapidly simulating repeated orbit satellite-borne natural scene SAR complex image data comprises the following steps:
firstly, determining coordinates of a central point of an imaging orbit and a central point of a ground scene according to the orbit parameters.
And secondly, reading in a ground natural scene DEM (digital Elevation model), laying scene ground points at equal intervals in longitude and latitude directions by taking a ground central point as a center, and iteratively calculating the position of a zero Doppler imaging satellite, the relative speed of the satellite and a ground scene point and an oblique distance vector corresponding to each scene point by adopting a quick method according to a radar RD equation.
Thirdly, simulating complex data of the SAR image; according to the imaging principle of a satellite-borne SAR satellite, obtaining an electromagnetic wave incident angle according to an oblique distance vector of each scene point and a normal vector of each small surface element of a ground scene, further calculating a backscattering coefficient of each scene point by using a backscattering coefficient and an empirical model of the electromagnetic wave incident angle, determining the pixel position of each scene point on an image by combining the length of the oblique distance and the imaging time with the SAR satellite azimuth resolution and the distance resolution for each scene point, then adding a random phase and an oblique distance phase after the backscattering coefficient of the point is opened to obtain complex data, adding the complex data of the scene point at the same pixel position, and then sequentially convolving with a distance and azimuth pulse compression result to obtain complex image data.
Fourthly, simulating the repeated orbit SAR image complex data with controllable base length; and taking the vector of the unit direction of the central slope of the SAR satellite as the direction of a horizontal base line, taking the vector of the central slope of the SAR satellite as the direction of a vertical base line according to the speed direction of the central position and the direction of the slope as vector cross multiplication, taking the vector sum of the horizontal base line and the vertical base line as the base line vector, controlling the satellite imaging orbit region to carry out corresponding deviation, repeating the second step and the third step on the original ground scene or the ground scene added with a deformation field, and generating the repeated orbit spaceborne SAR complex image data with a certain base line.
The invention has the beneficial effects that:
the method provided by the invention simulates the SAR satellite operation orbit, and simulates the ground scene according to the spaceborne SAR satellite imaging principle and the SAR satellite single-view complex image signal model to directly obtain the multiple-orbit SAR complex image data. A rapid method is adopted to iteratively calculate the zero Doppler imaging position of the satellite to obtain the slant range information, a simplified scattering model is utilized to calculate the backscattering coefficient, a simplified repeated orbit model is provided to generate any multiple SAR complex image data with controllable base line length, and the ground scene added with a deformation field can be simulated to obtain the deformed SAR complex image data. The traditional echo simulation method simulates pulse compression to obtain interference data, the calculation amount is huge, and especially for a complex natural scene with dense ground points, the time consumption is more huge. The method overcomes the defect of low speed of the traditional echo simulation method, shortens the simulation time by adopting the method for calculating the satellite zero Doppler imaging position by fast iteration, has high simulation precision, and truly embodies various factors such as backscattering effect, noise influence, shielding effect, top-bottom effect and the like. The method not only can provide complete complex image data and various auxiliary parameters like a real SAR satellite (such as a TerrasAR), but also can provide prior information with prior information such as control point deformation, deformation field range and size and the like for InSAR processing. The accuracy and convenience of the invention are fully verified after actual InSAR treatment.
Drawings
FIG. 1 is a flow chart of a method for rapidly simulating SAR complex image data of a repetitive orbit satellite-borne natural scene according to the invention.
Fig. 2 is a schematic diagram of the spatial geometric relationship between the satellite-borne SAR satellite and the laid ground natural scene in the second step of the present invention.
Fig. 3 is a geometrical diagram illustrating the calculation of the backscattering coefficient of the scene point in the third step of the present invention, wherein fig. 3(a) is a geometrical relationship of the facet element, and fig. 3(b) is a geometrical relationship of the normal vector and the incident angle.
Fig. 4 shows the image result of the simulation of the complex image data, in which fig. 4(a) shows a first simulation image (primary image) and fig. 4(b) shows a repetitive orbit simulation image (secondary image).
FIG. 5 is an interference result graph of two simulated complex image data.
FIG. 6 is a statistical histogram of interference coefficients for two simulated complex image data.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
As shown in fig. 1, the main process of the repeated orbit satellite-borne natural scene SAR complex image data rapid simulation method of the present invention includes the following steps:
reading in orbit parameters, SAR satellite parameters, ground natural scene parameters and image parameters, and determining a satellite orbit imaging center position and a corresponding zero Doppler imaging ground scene center position:
1.1, reading a parameter file in txt format, wherein the satellite orbit parameters comprise a near-center point angular distance omega, an orbit inclination angle i, an orbit semimajor axis a, a rising intersection point right ascension omega, an orbit eccentricity e and an orbit regression pipeline radius; the SAR satellite parameters include wavelength λ, bandwidth Bw, sampling rate fs, ideal repetition frequency Prf, pulse width τ, downward view angle θlAzimuthal resolution ρaAnd distance resolution ρr(ii) a The ground natural scene parameters comprise the number of control points and the central latitude lat of the scenecenterCounting the number of the azimuth DEM points, counting the number of the distance DEM points and spacing the distance DEM grids; the image parameters include the total number of images, the maximum amount of deformation between each image.
And 1.2, calculating the corresponding satellite imaging center moment according to the scene center latitude. The average angular velocity of the satellite motion isWherein, mu is 3.986013E +14 as the gravity parameter of the earth.
Included angle between intersatellite point plane and beam central intersection point planeComprises the following steps:
wherein Ea is 6378137.0 is the earth's semi-major axis.
Then the true paraxial angle θ corresponding to the simulated central time is:
the eccentric angle E corresponding to the simulation center moment is as follows:
imaging center time TcenterComprises the following steps:
the track radius r is:
further, the center time is obtainedCoordinates (x) of the star in the orbital plane coordinate systemvs,yvs,zvs) Comprises the following steps:
the satellite coordinates are converted from an orbit plane coordinate system to a non-rotating geocentric coordinate system according to the transformation matrix, and then the non-rotating geocentric coordinate system is converted to a rotating geocentric coordinate system, so that the three-dimensional coordinates (x) of the imaging center moment of the satellite under the rotating geocentric coordinates can be obtaineds,ys,zs)。
1.3, calculating longitude and latitude coordinates of the center point of the ground scene, firstly setting a unit direction vector (0,1,0) of the ground target in an antenna coordinate system, and then converting the unit direction vector into a rotating geocentric coordinate system (x)1,y1,z1) And calculating a center slope distance vector:
where Eb is 6356752.3141, the coordinate (x) of the center point of the ground scene in the rotating ground center coordinate systemt,yt,zt) Comprises the following steps:
then converted to longitude and latitude coordinates (lon) according to the following formulat,latt)：
Where e2 is 0.00669438003551279091 is the square of the first radius of curvature of the earth.
And secondly, reading in a ground natural scene DEM, laying scene ground points at equal intervals in longitude and latitude directions by taking a ground scene central point as a center, and iteratively calculating the position, the relative speed and the slant range vector of the zero Doppler imaging satellite corresponding to each scene point by adopting a quick method according to a radar RD equation.
And 2.1, reading the natural scene DEM file in the dat format, wherein the read scene DEM needs to be subjected to interpolation in advance, and the interval between each DEM point needs to ensure that at least 4 points exist in each resolution unit. And (3) laying the read DEM data along the direction of the longitude dimension according to the grid interval, namely, the data of the same row of the DEM is at the same latitude, and the data of the same column in the DEM is at the same longitude. And converting the longitude lon, latitude lat and elevation h of each point into a rotating geocentric coordinate system (x) according to the following formulat,yt,zt) Coordinates are as follows:
2.2 calculating N by extending left and right with the satellite imaging center time obtained in the first step as the center and the reciprocal 1/Prf of the repetition frequency as an interval timesOne satellite position (guaranteed to cover the ground scene range, at least 4001 satellite positions for a 3x3 km scene, NsOdd numbers are taken to make the number of satellites on the left side and the right side of the central moment the same), and the calculation method comprises the following steps:
track start time TminComprises the following steps:
Tmin＝Tcenter-(Ns-1)/2/Prf (11)
the average proximal angle M for the nth satellite position is:
M＝n*(i/Prf+Tmin) (12)
the eccentric angle E is:
the true paraxial angle θ is then found to be:
then, the coordinate (x) of the Nth satellite position in the rotating earth coordinate is obtained according to the method for calculating the satellite position of the imaging center moment in 1.2s,ys,zs)。
The velocity of the satellite in the orbital plane coordinate system is (v)xs_o,vys_o,vzs_o)：
The satellite velocity is translated from the orbital plane coordinate system to the non-rotating geocentric coordinate system by:
will NsThe three-dimensional coordinates and velocity vectors of each satellite position are stored for iterative computation of the zero doppler imaging position.
Setting four variables, namely, Satenum1, Satenum2, Satenum min, Satenum max, Satenum gap, Satenum1, a zero doppler imaging satellite position corresponding to a first point in each row of a ground scene point, Satenum2, a zero doppler imaging satellite position corresponding to a previous scene point in the same row, a Satenum min satellite position as a traversal starting point, a Satenum max as a traversal end point, and a Satenum gap as a traversal satellite position total number, wherein the four variables mutually satisfy the following relations:
for the first point in the first line of the natural scene (i.e. the point with the smallest longitude and the largest latitude), the speed of the first point without rotating the geocentric coordinate is determined as follows:
wherein Er is 6371140.0 is the radius of the spherical model of the earth, and SatenumMin is 0 and SatenumMax is NsFor the Nth satellite position of SatenumMin < N < SatenumMax, the relative speed with the ground point is the speed (v) under the rotating earth center coordinate systemxs,vys,vzs) Comprises the following steps:
the slope distance vector with the ground point is as follows:
according to the space geometric relationship between the satellite-borne SAR satellite and the distributed ground natural scene shown in figure 2, the Doppler frequency f between the position of the Nth satellite and the ground point is calculated by using the Doppler equationd：
Wherein lambda is the wavelength of the SAR satellite, and all N are calculated in an iterative mannersF of one satellite positiondTaking the satellite position N corresponding to the minimum value as a parametermin11As the imaging satellite position of this point, let satenu 1 be Nmin11,Satenum2＝Nmin11。
Then calculating the second point of the first line, updating the values of SatenumMin and SatenumMax, and traversing the calculation[SatenumMin,SatenumMax]F corresponding to satellite position indTaking the satellite position N corresponding to the minimum valuemin12As the imaging satellite position of this point, let satenu 2 be Nmin12. And (4) solving the position of the corresponding zero Doppler imaging satellite of the first row of the ground scene by the same method.
When calculating the first point of the second row, let Satenum2 be Satenum1, update the values of SatenumMin and SatenumMax, and go through the calculation fdMinimum position Nmin21And let Satenum1 be Satenum2 be Nmin12And iteratively calculating the zero Doppler imaging satellite position corresponding to the ground point of the second row by using the method for calculating the first row. And by analogy, calculating the zero Doppler imaging satellite positions, the relative speeds and the slant distance vectors corresponding to all the ground scene points.
Thirdly, simulating SAR imaging complex data; according to the imaging principle of a satellite-borne SAR satellite, calculating a slant range vector of each scene point and a normal vector of each small surface element of a ground scene to obtain an electromagnetic wave incident angle, further calculating a backscattering coefficient of each scene point by using a backscattering coefficient and an empirical model of the electromagnetic wave incident angle, determining the pixel position of each scene point on an image by combining the length of the slant range and the imaging time with the SAR satellite azimuth resolution and the distance resolution for each scene point, then adding a random phase and a slant range phase after the backscattering coefficient of the point is opened to obtain complex data, adding the complex data of the scene point at the same pixel position, and then sequentially convolving with a distance and azimuth pulse compression result to obtain complex image data.
3.1 calculating a backscattering coefficient; consider a number of adjacent data points of a distributed ground scene point as one facet element tangent to the scene surface as shown in fig. 3 (a). For a scene point with the coordinate of (m, n) of a non-edge point, the three-dimensional coordinate of the scene point is (x)t,yt,zt) Subtracting the three-dimensional coordinates of the (m-1, n-1) point to obtain a vectorSubtracting the three-dimensional coordinates of the (m-1, n) point to obtain a vectorTo pairCross multiplication is carried out to obtain a normal vector of a small surface elementThen obtain the resultThe slope distance vector of the pointAngle therebetweenI.e., the incident angle of the electromagnetic wave, as shown in fig. 3 (b).
Obtaining backscattering coefficients sigma corresponding to different incidence angles according to the following empirical model:
3.2 obtaining image complex data; considering the SAR system and the imaging process as a linear system, the SAR single view complex image can be represented as a convolution of the ground target scattering coefficient times the phase term due to the relative distance between the radar and the target, and then the successive distance and azimuth pulse compression results.
For a ground scene point, the corresponding zero Doppler imaging satellite serial number is N (0 < N)s) The vector of the skew angle isLength of skewThe pixel coordinates (Ix, Iy) on the SAR image are then:
wherein N is0Zero Doppler imaging satellite sequence number, R, corresponding to ground scene center point0Is the length of the slope between the center point and the position of the scene, rhorC/2fs is the range-to-sample distance of the SAR satellite (fs is the satellite sampling frequency, c is the speed of light), and ShiftRange, ShiftAzimath is half the total row and column number of the image, respectively.
The complex data Comp corresponding to the ground scene point is:
where comp.re is the real part, comp.im is the imaginary part,is a random phase angle.
And (4) performing iterative calculation on all the ground scene points, and accumulating the complex data of the ground points with the same pixel coordinate.
Then, for the complex data matrix of the image obtained in the previous step andfunction sumAnd carrying out convolution operation on the function to obtain complex data of the simulated SAR image. Wherein,sampling range for SAR satellite azimuthAs the center point of the scene and the ZedopuRelative velocity vectors between the locations of the imaging satellites).
Fourthly, simulating the repeated orbit SAR image complex data with controllable base length; for the repeated orbit, because the deviation of the regression baseline is not large every time, and the length of the imaging orbit is relatively short, the simulation result of the repeated orbit with the controllable baseline length can be generated by a simplified method.
Calculating a unit direction vector of the central slope of the SAR satellite as a horizontal baseline direction, performing cross multiplication according to the speed direction of the central position and the slope direction to obtain a vertical baseline direction, performing linear combination of vectors of the horizontal baseline and the vertical baseline as a baseline vector, controlling the first satellite imaging orbit region to perform corresponding offset, repeating the second step and the third step on the original ground scene or the ground scene added with a deformation field, and generating repeated orbit spaceborne SAR complex image data with a certain baseline.
4.1 calculating a baseline vector; taking the slant distance vector between the scene central point and the zero Doppler imaging satellite position corresponding to the scene central pointAs a horizontal baseline direction vectorRelative velocity vector corresponding to scene central pointAndperforming vector cross multiplication and taking the unit direction vector of the result to obtain the direction vector of the vertical baselineThen the baseline vector isWherein B is||,B⊥Are respectively parallelA baseline length and a vertical baseline length.
For N obtained in the second stepsThree-dimensional coordinates (x) of satellite position of imaging orbits,ys,zs) Adding the baseline vector to obtain N of the first regression orbitsThe position of each imaging satellite is three-dimensional coordinate.
And repeating the second step and the third step to generate the simulated SAR image data of the regression orbit. If the DEM data read in the second step is the original DEM data, no deformation occurs between the generated images, and the generated images can be used for InSAR processing; and if the read DEM data is added with a deformation field, the generated images have deformation information and can be used for D-InSAR processing.
Fig. 4 shows images of complex image data obtained by the first and second simulation imaging, where fig. 4(a) is a first simulation image (main image), fig. 4(b) is a repeated orbit simulation image (auxiliary image), bright spots in the images are control points arranged at equal intervals in a ground scene, fig. 5 is an interference image obtained by interference processing of the two complex images, and fig. 6 is an interference coefficient statistical histogram of the two simulation complex image data, and it is verified by subsequent actual processing that the simulation complex image data can be used for InSAR and D-InSAR processing.
Claims (4)
1. A repeated orbit satellite-borne natural scene SAR complex image data rapid simulation method is characterized by comprising the following steps:
firstly, determining coordinates of an imaging track central point and a ground scene central point according to track parameters;
reading in a ground natural scene DEM (digital Elevation model), laying scene ground points at equal intervals in longitude and latitude directions by taking a ground central point as a center, and iteratively calculating the position of a zero Doppler imaging satellite, the relative speed of the satellite and a ground scene point and an oblique distance vector corresponding to each scene point by adopting a quick method according to a radar RD equation;
thirdly, simulating complex data of the SAR image; according to the imaging principle of a satellite-borne SAR satellite, obtaining an electromagnetic wave incident angle according to an oblique distance vector of each scene point and a normal vector of each small surface element of a ground scene, further calculating a backscattering coefficient of each scene point by using a backscattering coefficient and an empirical model of the electromagnetic wave incident angle, determining the pixel position of each scene point on an image by combining the length of the oblique distance and the imaging time with the SAR satellite azimuth resolution and the distance resolution for each scene point, then adding a random phase and an oblique distance phase after the backscattering coefficient of each scene point is opened to obtain complex data, adding the complex data of the scene point at the same pixel position, and then sequentially convolving with SAR and an azimuth pulse compression result to obtain complex image data;
fourthly, simulating the repeated orbit SAR image complex data with controllable base length; and taking the vector of the unit direction of the central slope of the SAR satellite as the direction of a horizontal base line, taking the vector of the central slope of the SAR satellite as the direction of a vertical base line according to the speed direction of the central position and the direction of the slope as vector cross multiplication, taking the vector sum of the horizontal base line and the vertical base line as the base line vector, controlling the satellite imaging orbit region to carry out corresponding deviation, repeating the second step and the third step on the original ground scene or the ground scene added with a deformation field, and generating the repeated orbit spaceborne SAR complex image data with a certain base line.
2. The method for rapidly simulating the SAR complex image data of the repetitive orbit satellite-borne natural scene according to claim 1, which is characterized in that: in the second step, the following method is adopted for calculating the zero Doppler imaging satellite position, the relative speed between the satellite and the ground scene point and the slant distance vector corresponding to each scene point:
2.1 reading natural scene DEM files in dat format, wherein the read scene DEM needs to be interpolated in advance, the interval between each DEM point needs to ensure that at least 4 points are arranged in each resolution unit, the read DEM data is distributed along the direction of a through dimension according to the grid interval, namely the data of the same row of the DEM is at the same latitude, the data of the same column in the DEM is at the same longitude, and each DEM is arranged according to the following formulaThe longitude lon, latitude lat and elevation h of the point are converted into a rotating geocentric coordinate system (x)t,yt,zt) Coordinates where Ea 6378137.0 is the earth's semi-major axis, e2 0.00669438003551279091 is the square of the earth's first radius of curvature:
2.2 calculating N by using the reciprocal 1/Prf of the repetition frequency as an interval time and extending left and right by taking the satellite imaging center time as the centersThe satellite position is calculated by the following method:
track start time TminComprises the following steps:
Tmin＝Tcenter-(Ns-1)/2/Prf (2)
the average proximal angle M for the nth satellite position is:
M＝n*(i/Prf+Tmin) (3)
the eccentric angle E is:
where e is the track eccentricity, then find the true paraxial angle θ as:
further, the coordinates (x) of the Nth satellite in the orbital plane coordinate system are obtainedvs,yvs,zvs) Comprises the following steps:
wherein r is an orbit vector, and the coordinate of the Nth satellite in the orbit plane coordinate system is converted into the rotating geocentric coordinate system according to the coordinate system conversion matrix, so that the three-dimensional coordinate (x) of the Nth satellite in the rotating geocentric coordinate system can be obtaineds,ys,zs)；
The velocity of the satellite in the orbital plane coordinate system is (v)xs_o,vys_o,vzs_o)：
The satellite speed is converted from an orbital plane coordinate system to a non-rotating earth center coordinate system by the following operations, wherein mu-3.986013E +14 is an earth gravity parameter, omega is a near center angular distance, i is an orbital inclination angle, a is an orbital semimajor axis, and omega is a rising intersection right ascension:
will NsStoring three-dimensional coordinates and velocity vectors of the satellite positions so as to iteratively calculate a zero Doppler imaging position;
setting five variables, namely, Satenum1, Satenum2, Satenum min, Satenum max and Satenum gap, wherein Satenum1 is a zero doppler imaging satellite position corresponding to a first point in each row of a ground scene point, Satenum2 is a zero doppler imaging satellite position corresponding to a previous scene point in the same row, the Satenum min satellite position is a traversal starting point, the Satenum max is a traversal end point, and the Satenum gap is a total number of traversal satellite positions, and the following relations are satisfied between each other:
for the first point in the first line of the natural scene, i.e. the point with the smallest longitude and the largest latitude, the speed of the first point in the non-rotating geocentric coordinate is calculated as follows:
wherein Er is 6371140.0 is the radius of the spherical model of the earth, and SatenumMin is 0 and SatenumMax is NsFor the Nth satellite position of SatenumMin < N < SatenumMax, the relative speed with the ground point is at the center of the rotating earthVelocity (v) in a coordinate systemxs,vys,vzs) Comprises the following steps:
the slope distance vector with the ground point is as follows:
according to the space geometric relationship between the satellite-borne SAR satellite and the distributed ground natural scene, the Doppler frequency f between the position of the Nth satellite and the ground point is calculated by using the Doppler equationd：
Where λ is the radar wavelength, iteratively calculating all NsF of one satellite positiondTaking the satellite position N corresponding to the minimum value as a parametermin11The imaging satellite position as the ground point is specified by Satenum1 ═ Nmin11,Satenum2＝Nmin11；
Next, calculate the second point of the first row, update the values of SatenumMin, SatenumMax, traverse the calculation [ SatenumMin, SatenumMax]F corresponding to satellite position indTaking the satellite position N corresponding to the minimum valuemin12As the imaging satellite position of this point, let satenu 2 be Nmin12The position of a point corresponding to a zero Doppler imaging satellite in a first row of a ground scene is calculated by the same method;
when calculating the first point of the second row, let Satenum2 be Satenum1, update the values of SatenumMin and SatenumMax, and go through the calculation fdMinimum position Nmin21And let Satenum1 be Satenum2 be Nmin12And iteratively calculating the position of the zero Doppler imaging satellite corresponding to the ground point in the second row by using a method for calculating the first row, and calculating the position, the relative speed and the slant distance vector of the zero Doppler imaging satellite corresponding to all the ground scene points by analogy.
3. The method for rapidly simulating the SAR complex image data of the repetitive orbit spaceborne natural scene according to claim 1, wherein the method for calculating the backscattering coefficient of the ground scene point and simulating the SAR complex image data in the third step comprises the following steps:
3.1 calculating a backscattering coefficient; regarding a plurality of adjacent data points of the distributed ground scene points as a small surface unit tangent to the surface of the scene, and regarding the scene point with the non-edge point and the coordinate of (m, n), the three-dimensional coordinate of the scene point is (x)t,yt,zt) Subtracting the three-dimensional coordinates of the (m-1, n-1) point to obtain a vectorSubtracting the three-dimensional coordinates of the (m-1, n) point to obtain a vectorTo pairCross multiplication is carried out to obtain a normal vector of a small surface elementThen obtain the resultThe diagonal distance vector of the scene point with the coordinate (m, n)Angle therebetweenNamely the incident angle of the electromagnetic wave;
obtaining backscattering coefficients sigma corresponding to different incidence angles according to the following empirical model:
3.2 obtaining image complex data; considering the SAR system and the imaging processing as a linear system, the SAR single-vision complex image can be expressed as a convolution of a ground target scattering coefficient multiplied by a phase term caused by the relative distance between a radar and a target and then a distance and azimuth pulse compression result;
for a ground scene point, the corresponding zero Doppler imaging satellite serial number is N (0 < N)s) The vector of the skew angle isLength of skewThe pixel coordinates (Ix, Iy) on the SAR image are then:
wherein N is0Zero Doppler imaging satellite sequence number, R, corresponding to ground scene center point0Is the length of the slope between the center point and the position of the scene, rhorC/2fs is the distance direction sampling distance of the SAR satellite, fs is the satellite sampling frequency, c is the light speed, and ShiftRange and ShiftAzimath are respectively half of the total row number and the total column number of the image;
the complex data Comp corresponding to the ground scene point is:
where comp.re is the real part, comp.im is the imaginary part,is a random phase angle;
iteratively calculating all ground scene points, and accumulating the complex data of the ground points with the same pixel coordinate;
then the obtained images are alignedA plurality of data matrices andfunction sumThe function is convoluted to obtain complex data of the simulated SAR image, wherein,for the SAR satellite azimuth sampling range,is the relative velocity vector between the scene centroid and the zero doppler imaging satellite position.
4. The method for rapidly simulating the SAR complex image data of the repetitive orbit spaceborne natural scene as claimed in claim 1, characterized in that the SAR complex image data of the repetitive orbit with controllable length of the simulation base line adopts the following method:
4.1 calculating a baseline vector; taking the slant distance vector between the scene central point and the zero Doppler imaging satellite position corresponding to the scene central pointAs a horizontal baseline direction vectorRelative velocity vector corresponding to scene central pointAndperforming vector cross multiplication and taking the unit direction vector of the result to obtain the direction vector of the vertical baselineThen the baseline vector isWherein B is||,B⊥The length of the parallel base line and the length of the vertical base line are respectively;
for N obtained in the second stepsThree-dimensional coordinates (x) of satellite position of imaging orbits,ys,zs) Adding the baseline vector to obtain N of the first regression orbitsThree-dimensional coordinates of the position of each imaging satellite;
then repeating the second and third steps to generate simulated SAR image data of the regression orbit, if DEM data read in the second step is original DEM data, no deformation occurs between the generated images, and the generated images can be used for InSAR processing; and if the read DEM data is added with the deformation field, the generated images have deformation information and can be used for D-InSAR processing.
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Application publication date: 20160615 Assignee: Shanghai Spaceflight Institute of TT&C And Telecommunication Assignor: BEIHANG University Contract record no.: X2021990000219 Denomination of invention: A fast simulation method for complex image data of repeated orbit spaceborne natural scene SAR Granted publication date: 20181225 License type: Common License Record date: 20210413 |