CN117269911A - Spaceborne distributed InSAR interference calibration method - Google Patents
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Abstract
The invention provides a satellite-borne distributed InSAR interference calibration method, which belongs to the technical field of radar signal processing, and aims to independently solve interference errors by separately establishing calibration models of interference parameters, reduce error coupling between the interference parameters, and more accurately estimate the interference parameters without being influenced by errors of other parameters. The invention is suitable for the one-time multi-time operation mode of the distributed SAR system.
Description
Technical Field
The invention belongs to the technical field of radar signal processing, and particularly relates to a satellite-borne distributed InSAR interference calibration method.
Background
Interferometric synthetic aperture radar (Interferometric Synthetic Aperture Radar, inSAR) uses the difference in echo phase of the returning satellites to accurately calculate terrain and elevation data for the target region by performing an interferometric process using two or more SAR images. The distributed SAR system is a satellite system consisting of two or more satellites, radar transmitting and receiving equipment is loaded on each satellite, different applications are realized through cooperative work among the satellites, and the distributed SAR system is a large system with high complexity and multiple structural layers, and can replace the function of one large satellite in the whole. The spaceborne distributed InSAR is a spaceborne earth observation system combining InSAR technology and satellite formation technology. Compared with a satellite loading orbit InSAR system and a single-satellite platform double-antenna InSAR system, the satellite loading orbit InSAR system has outstanding advantages in the aspect of inversion of high-precision DEM (Digital Elevation Model, digital ground elevation model). DEM is critical for many areas of commercial and scientific application such as hydrology, glaciology, geology and forestry, etc.
In the process of inversion of DEM products by interferometric processing, various unavoidable errors exist in the spaceborne distributed InSAR system. These interference error parameters include tilt, stage position, absolute interference phase offset, and baseline length. These errors can have an impact on the interference performance of the system and can affect the quality of the final DEM product. These interference error parameters must be scaled and compensated for in order to obtain an accurate DEM product.
The existing spaceborne distributed InSAR interference calibration technical scheme mainly has two problems:
1. not applicable to distributed SAR systems: the current spaceborne InSAR interference scaling technology is mainly designed for a single-base SAR system. In general, a single-base SAR system adopts a single-transmission single-reception working mode, while a distributed SAR system adopts a single-transmission multi-reception mode, wherein one satellite is used as a main satellite to transmit electromagnetic waves, and the other satellites are used as auxiliary satellites to only receive signals. The difference of the working modes of the two systems makes the existing single-base SAR interference scaling method not directly applicable to the distributed SAR system, thereby limiting the performance and application fields of the method.
2. Interference parameter error coupling problem: the current commonly used spaceborne InSAR interferometry calibration method is to establish polynomial equations based on a three-dimensional reconstruction model, and estimate interference parameter errors by jointly solving the equations. However, this approach tends to result in error coupling between the interference parameters, i.e., the error of one parameter affects the estimation of the other parameter, such that the final error result does not accurately reflect the true systematic error. Therefore, to solve the problem of error decoupling, a more sophisticated interferometric scaling model and interferometric scaling procedure needs to be built to ensure accuracy and reliability.
Disclosure of Invention
In order to solve the technical problems, the invention provides a satellite-borne distributed InSAR interference calibration method, which is characterized in that calibration models of interference parameters are separately established, interference errors are independently solved, error coupling among the interference parameters is reduced, and the interference parameters are estimated more accurately without being influenced by errors of other parameters. The invention is suitable for the one-time multi-time operation mode of the distributed SAR system.
In order to achieve the above purpose, the invention adopts the following technical scheme:
step 1: determining calibration parameters of satellite-borne distributed InSAR interference calibration, wherein the calibration parameters comprise main star slope distance, main star azimuth time, auxiliary star slope distance, auxiliary star azimuth time, interference phase and baseline vector;
step 2: establishing a main star slope and main star azimuth time calibration model, and solving the main star slope and main star azimuth time errors, so as to obtain accurate main star slope and main star azimuth time;
step 3: establishing an auxiliary star chute and auxiliary star azimuth time calibration model, and solving auxiliary star chute and auxiliary star azimuth time errors so as to obtain accurate auxiliary star chute and auxiliary star azimuth time;
step 4: establishing an absolute interference phase offset model, and solving an absolute interference phase error, so as to obtain an accurate interference phase;
step 5: establishing a baseline calibration model;
step 6: and solving the baseline error, thereby obtaining an accurate baseline vector.
The beneficial effects are that:
(1) The invention reduces the error coupling between interference parameters, solves the problem of error coupling between interference parameters by separately establishing the calibration model of the interference parameters and independently solving the interference errors, and is beneficial to more accurately estimating the interference parameters without being influenced by errors of other parameters. The present invention also details the scaling sequence of each interferometric scaling parameter.
(2) The invention is applicable to distributed SAR systems. The method is specially designed for the distributed SAR system, and is suitable for a one-time and multi-time working mode of the distributed SAR system.
Drawings
Fig. 1 is a flow chart of a satellite-borne distributed InSAR interference calibration method of the present invention.
FIG. 2 is a schematic diagram of a main star skew and azimuth time scaling model.
FIG. 3 is a schematic diagram of an auxiliary star skew and azimuth time scaling model.
Fig. 4 is a schematic diagram of a baseline calibration model.
Detailed Description
The invention will now be described in detail by way of example with reference to the accompanying drawings.
As shown in fig. 1, the spaceborne distributed InSAR interference calibration method of the present invention includes the following steps:
step 1, determining scaling parameters of spaceborne distributed InSAR interferometry scaling:
the calibration parameters directly influence the accuracy and reliability of the InSAR inversion elevation, and comprise a main star slope, main star azimuth time, auxiliary star slope, auxiliary star azimuth time, interference phase and a base line vector. The main star inclined distance is the nearest inclined distance from the main star to the ground target of the corresponding SAR image, the main star azimuth time is the imaging start time of the main star SAR image, the auxiliary star inclined distance is the nearest inclined distance from the auxiliary star to the ground target of the corresponding SAR image, the auxiliary star azimuth time is the imaging start time of the auxiliary star SAR image, the interference phase is the phase difference between radar wave echoes of the main star and the auxiliary star, and the baseline vector is the vector difference between the main star and the auxiliary star when the main star and the auxiliary star image the same ground point.
Step 2, establishing and solving a main star skew and azimuth time scaling model, which comprises the following steps:
solving the time error of the main star slope distance and the azimuth direction to obtain the accurate main star slope distance and the azimuth direction time.
The main star slope distance and azimuth time scaling model is built based on the main star observation geometric schematic diagram shown in fig. 2. In FIG. 2, the main star is according to the flyThe line track flies, a plurality of pulse signals are transmitted to the ground to form a pulse sequence, the signals return through the receiving process after reaching the ground target through the transmitting process, and the SAR receives the returned echo signals in the receiving window. Starting time in the direction of the main starAnd nearest skew time->As calibration parameters, the skew, azimuth time calibration parameter vector of the main star is obtained>。
Inputting a main star SAR image, wherein a calibration point exists on the image, and the pixel position of the image corresponding to the calibration point is that，/>For azimuth coordinates>Is distance-wise coordinate. Then the SAR imaging time of the azimuth time domain and the distance time domain corresponding to the calibration point can be obtained>And->The method comprises the following steps of:
，
wherein,for azimuth time sampling interval, +.>For picking upSample window start time, +.>Is the distance-to-time sampling interval. The azimuth time sampling interval, the sampling window starting time and the distance time sampling interval can be read from SAR image auxiliary data.
Then the slant distance from the main star to the calibration point can be obtainedThe method comprises the following steps:
，
wherein,is the speed of light.
The Doppler frequency between the principal star and the calibration point is:
，
wherein,for radar wave wavelength, < >>To coordinate the three-dimensional position coordinates of the calibration points,for the three-dimensional coordinates of the position of the main star under the imaging time corresponding to the calibration point, the +.>And (5) the velocity vector of the main star under the imaging time corresponding to the calibration point. Therefore, the imaging time is +.>At the time, the three-dimensional coordinates and the speed of the position of the ground point object observed by the main star are +.>Andthe specific expression is:
，
wherein,，/>and->Is the polynomial parameter of the main star track, which can be obtained by the auxiliary information of the main star image, <' > and the polynomial parameter of the main star track>The degree of the polynomial is here set to 3. Because of the main star azimuth start time->And nearest skew time->And if errors exist, the obtained distance from the main star to the calibration point and the Doppler frequency between the main star and the calibration point are both errors.
The true slant distance from the main star to the calibration point can be obtained according to the three-dimensional position coordinates of the calibration point and the main starThe method comprises the following steps:
，
true Doppler frequencyCan be used forDerived from the image assistance data.
Thus, the simultaneous range equation and the Doppler frequency equation build a scaled model of the principal star as:
，
wherein,is a scaling equation derived from the pitch parameters, < ->Is a scaling equation derived from the doppler parameters. Association->And->Solving the accurate main star slant distance and azimuth time. And solving the scaling model by adopting a least square iteration method. Specifically, in iteration +.>The calculation formula of the steps is as follows:
，
wherein,indicate->Values of parameters in the frame for the time of iteration, +.>Indicate->For multiple iterations->Value of->Representing the rate of change of skew error with the starting time of the azimuth of the main star, +.>Representing the rate of change of skew error with the latest skew time of the main star, < >>Indicating the rate of change of doppler frequency error with the start time of the principal star bearing,the rate of change of the doppler frequency error with the time of the last range of the principal star is shown. The termination condition of the iteration is that。
Step 3, establishing and solving an auxiliary star chute and azimuth time scaling model, which comprises the following steps:
solving the time errors of the auxiliary star chute and the azimuth direction so as to obtain the accurate auxiliary star chute and the accurate auxiliary star azimuth direction time.
The range and azimuth time scaling model of the auxiliary star is established based on the auxiliary star observation geometric schematic diagram of fig. 3. Start time with satellite orientationAnd nearest skew time->As calibration parameters, the vector of the time calibration parameters of the skew, azimuth and azimuth of the auxiliary star is obtained>。
Inputting an auxiliary SAR image, wherein scaling points exist on the image, and the pixel positions of the image corresponding to the scaling points are as follows，For azimuth coordinates>Is distance-wise coordinate. From the auxiliary observation diagram of FIG. 3, it can be deduced that the auxiliary receiving time corresponding to the calibration point is +.>And main star emission time->The method comprises the following steps:
，
，
the main star transmits electromagnetic waves to the auxiliary star to receive the electromagnetic waves, and the time for the electromagnetic waves is as follows:
，
the path length that the auxiliary star receives the electromagnetic wave of the calibration point is:
，
the Doppler frequency of the calibration point is:
，
wherein,and->Respectively->Three-dimensional coordinates and velocity vector of the position of the moment main star,/->And->Are respectively +.>Three-dimensional coordinates and velocity vectors of the position of the auxiliary star at the moment. The relationship between the three-dimensional coordinates and the velocity vector of the position of the primary star and time is given in step 2, and the relationship between the three-dimensional coordinates and the velocity vector of the position of the secondary star and time is:
，
wherein,，/>and->The auxiliary star track polynomial parameter can be obtained through the image auxiliary information of the main star. Because of the main star azimuth start time->And nearest skew time->If errors exist, errors exist in the obtained echo process, the main satellite and the Doppler frequency.
The real echo process can be obtained according to the three-dimensional position coordinates of the calibration points and the main and auxiliary satellites. True Doppler frequency +.>Can be derived from the auxiliary star image auxiliary data. Thus, the simultaneous range equation and the Doppler frequency equation build a scaling model of the satellite as:
，
wherein,is a scaling equation derived from the pitch parameters, < ->Is a scaling equation derived from the doppler parameters. Association->And->Solving accurate auxiliary star slant distance and azimuth time. And solving the scaling model by adopting a least square iteration method. Specifically, in iteration +.>The calculation formula of the steps is as follows:
，
wherein,indicate->For multiple iterations->Value of->Indicating that the skew error starts along with the azimuth direction of the auxiliary starRate of change of onset->Representing the rate of change of the firing skew error with the last skew time of the satellite, +.>Representing the rate of change of Doppler frequency error with satellite bearing direction start time, < >>The rate of change of the doppler frequency error with the last ramp time of the satellite is shown. The termination condition of the iteration is->。
Step 4: establishing and solving an interference phase scaling model, comprising: and solving the interference phase error.
Interference phase errorDue to the difference in transmit and receive channels between the two stars. The specific absolute interferometric phase offset model is established as:
，
wherein,for interference phase shift +.>For the flat ground phase>For unwrapping phase, these two parameters are derived from the spaceborne distributed InSAR interferometric processing plug-in. Wherein->2, correcting the azimuth time of the main star in the step 2, and then observing the position of the ground point by the main star, wherein +.>And (3) correcting the azimuth time of the auxiliary star in the step 3, and observing the position of the ground point by the auxiliary star.
Since the unwrapping phase also contains an interference phase error of a multiple of 2 pi whole period caused by the fuzzy number, and the time synchronization can possibly introduce an interference phase error with pi, the unwrapping phase needs to be processedIn pi integer multiple of the absolute interference phase error +.>：
，
Wherein,representing rounding the input real numbers to the nearest integer. Thus, accurate interference phase +.>The method comprises the following steps:
，
wherein,is a fuzzy phase introduced due to the unwrapping process and time synchronization. n is a fuzzy number and is an integer.
Step 5: establishing a baseline calibration model:
determining the position of punctuation with primary astrologyEstablishing a coordinate system as an origin, defining the direction of the main star speed as a Y-axis, and directing the earth center to the mainThe direction of the star is taken as a Z axis, the orthogonal Y axis of the Z axis is taken as an X axis, and the unit direction vector of the three axes is as follows:
，
wherein,representing modulo the vector, ++>Representing vector cross-multiplication.
Calculating an initial baseline vector：
，
Calculating the lower view angle of the main star-view measurement punctuationThe method comprises the following steps:
，
wherein,for baseline dip +.>，/>For the exact pitch of the main star obtained in step 2, < > in->The exact interference phase obtained in step 4. The elevation of the calibration point can be obtained by the interference principle>The method comprises the following steps:
，
wherein,the radius of curvature of the earth corresponding to the ground calibration point.
The interference principle can give Gao Chenghui errors in the calibration points due to errors in the baseline. Because the baseline error in the Y direction generally has smaller influence on the elevation, the elevation error of the calibration point obtained by the interference principle is mainly caused by the baseline error in the X direction and the Z direction, and the calibration parameters of the baselines in the X direction and the Z direction are as followsAnd->. The baseline error may be obtained by solving for the elevation error introduced by the baseline.
Reference elevation according to calibration pointsElevation error of the interference principle can be calculated>The method comprises the following steps:
，
calculating parallel line of sight baseline errorsThe method comprises the following steps:
，
and 6, solving the baseline error. A baseline error solving diagram is shown in FIG. 4, and the baseline isBaseline error of. SAR images under two different angles of incidence are selected to be processed in the steps 2, 3, 4 and 5 respectively, and the elevation error is obtained according to the control elevation of the calibration point and the elevation generated by InSAR processing>Finally, through the elevation errorCalculating the incident angle->And->The lower parallel line of sight baseline errors are +.>And->。
Eventually, baseline errorThe method can be solved as follows:
，
finally, obtaining an accurate baselineThe method comprises the following steps:
，
in summary, the above embodiments are only preferred embodiments of the present invention, and are not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. The spaceborne distributed InSAR interference calibration method is characterized by comprising the following steps of:
step 1: determining calibration parameters of satellite-borne distributed InSAR interference calibration, wherein the calibration parameters comprise main star slope distance, main star azimuth time, auxiliary star slope distance, auxiliary star azimuth time, interference phase and baseline vector;
step 2: establishing a main star slope and main star azimuth time calibration model, and solving the main star slope and main star azimuth time errors, so as to obtain accurate main star slope and main star azimuth time;
step 3: establishing an auxiliary star chute and auxiliary star azimuth time calibration model, and solving auxiliary star chute and auxiliary star azimuth time errors so as to obtain accurate auxiliary star chute and auxiliary star azimuth time;
step 4: establishing an absolute interference phase offset model, and solving an absolute interference phase error, so as to obtain an accurate interference phase;
step 5: establishing a baseline calibration model;
step 6: and solving the baseline error, thereby obtaining an accurate baseline vector.
2. The method for calibrating the interference of the distributed InSAR according to claim 1, wherein in the step 1, the main star slope is the nearest slope distance from the main star of the corresponding SAR image to the ground target, the main star azimuth time is the imaging start time of the corresponding SAR image, the auxiliary star slope is the nearest slope distance from the auxiliary star of the corresponding SAR image to the ground target, the auxiliary star azimuth time is the imaging start time of the corresponding SAR image, the absolute interference phase is the phase difference between radar wave echoes of the main star and the auxiliary star, and the baseline vector is the inter-satellite vector difference of the main star and the auxiliary star when the main star and the auxiliary star image the same ground point.
3. The method for interference calibration of satellite-borne distributed InSAR according to claim 2, wherein the step 2 comprises:
starting time in the direction of the main starAnd nearest skew time->As calibration parameter, obtain the main star skew, main star azimuth time calibration parameter vector +.>；
Inputting a main star SAR image, wherein calibration points exist on the main star SAR image, and the positions of image pixels corresponding to the calibration points are as follows，/>For azimuth coordinates>Is a distance coordinate; SAR imaging time of azimuth time domain corresponding to calibration point is obtained>And SAR imaging time from time domain +.>The method comprises the following steps of:
，
wherein,time sampling interval for azimuth direction，/>For the sampling window start time, +.>Sampling intervals for distance to time; azimuth time sampling interval->Sampling window start time->And distance-to-time sampling intervalAre all obtained by reading SAR image auxiliary data;
the simultaneous distance equation and the Doppler frequency equation establish a main star slope distance and main star azimuth time scaling model as follows:
，
wherein,calibration equation of the main star according to the skew parameters,>calibration equation based on Doppler parameters, which is the dominant star,>for the three-dimensional position coordinates of the calibration points, +.>And->Time is +.>Three-dimensional coordinates and speed of the ground point target in the time main star observation position, +.>For the dominant star Doppler frequency, < >>For the speed of light->Is the wavelength of radar waves; association->And->Solving the accurate main star slope distance and main star azimuth time.
4. A method of spaceborne distributed InSAR interference scaling according to claim 3, wherein step 3 comprises:
start time with satellite orientationAnd nearest skew time->As calibration parameters, the auxiliary star skew, auxiliary star azimuth time calibration parameter vector +.>；
Inputting an auxiliary SAR image, wherein scaling points exist on the auxiliary SAR image, and the image pixel positions corresponding to the scaling points are as follows，/>For azimuth coordinates>Is a distance coordinate; auxiliary star receiving time corresponding to calibration point>And main star emission time->The method comprises the following steps:
，
，
the simultaneous distance equation and the Doppler frequency equation establish an auxiliary star chute and auxiliary star azimuth time scaling model as follows:
，
wherein,is the scaling equation of the auxiliary star based on the skew parameters,/->Is a calibration equation of the auxiliary star obtained according to Doppler parameters; />And->Respectively->Three-dimensional coordinates and velocity vectors of the location of the moment main star,and->Are respectively +.>Three-dimensional coordinates and velocity vector of the position of the moment auxiliary star,/->The auxiliary star Doppler frequency; association->And->Solving accurate auxiliary star slant distance and auxiliary star azimuth time.
5. The method for interference calibration of satellite-borne distributed InSAR according to claim 4, wherein the step 4 comprises:
the absolute interferometric phase offset model is built as:
，
wherein,for interference phase shift +.>For the flat ground phase>For unwrapping phase, +.>For the position of the main satellite observation ground point corrected for the main satellite azimuth time of step 2, +.>The position of the ground point is observed by the auxiliary star after the auxiliary star azimuth time correction in the step 3;
absolute interference phase errorThe method comprises the following steps:
，
wherein,representing rounding the input real numbers to the nearest integer;
accurate interference phaseThe method comprises the following steps:
，
wherein,is a blurred phase introduced due to the unwrapping process; />Is a fuzzy number and is an integer.
6. The method for interferometric calibration of on-board distributed InSAR according to claim 5, wherein the step 5 comprises:
calculating an initial baseline vector：
，
Calculating the lower view angle of the main star-view measurement punctuationThe method comprises the following steps:
，
wherein,for baseline dip +.>Is the main star slant distance; the elevation of the calibration point is obtained by the interference principle>The method comprises the following steps:
，
wherein,the earth curvature radius corresponding to the ground calibration point is set;
the baseline error is obtained by solving the elevation error introduced by the baseline:
reference elevation according to calibration pointsCalculating elevation error based on interference principle>The method comprises the following steps:
，
calculating baseline errors for parallel lines of sightThe method comprises the following steps:
。
7. the method for interferometric calibration of on-board distributed InSAR according to claim 6, wherein the step 6 comprises:
SAR images under two different angles of incidence are selected to be processed in the steps 2, 3, 4 and 5 respectively, and the elevation error is used for the SAR imagesRespectively calculating to obtain incidence angle->Baseline error of parallel line of sight +.>And incidence angle->Baseline error of parallel line of sight +.>；
Baseline errorThe solution is as follows:
，
obtaining accurate baseline vectorThe method comprises the following steps:
，
wherein,calibrating parameters for X-direction baseline,>parameters were calibrated for the Z-direction baseline.
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