CN112179314B - Multi-angle SAR elevation measurement method and system based on three-dimensional grid projection - Google Patents

Multi-angle SAR elevation measurement method and system based on three-dimensional grid projection Download PDF

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CN112179314B
CN112179314B CN202011024260.4A CN202011024260A CN112179314B CN 112179314 B CN112179314 B CN 112179314B CN 202011024260 A CN202011024260 A CN 202011024260A CN 112179314 B CN112179314 B CN 112179314B
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CN112179314A (en
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王志斌
张润宁
张庆君
刘杰
匡辉
李真芳
周超伟
于海锋
吕争
李堃
徐明明
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Beijing Institute of Spacecraft System Engineering
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C5/00—Measuring height; Measuring distances transverse to line of sight; Levelling between separated points; Surveyors' levels
    • 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
    • G01S13/9004—SAR image acquisition techniques
    • G01S13/9005—SAR image acquisition techniques with optical processing of the SAR signals

Abstract

The invention discloses a multi-angle SAR elevation measurement method based on three-dimensional grid projection, which comprises the steps of selecting a main image in a multi-angle SAR image sequence; searching a target elevation for each pixel in the main image to perform geometric registration on the multi-angle SAR image sequence, and determining registration offset of each auxiliary image; acquiring a multi-angle SAR image sequence according to the registration offset; calculating a joint correlation coefficient to obtain a change relation of the joint correlation coefficient along with the target elevation; and realizing the elevation measurement of the target by optimizing the searched target elevation when the joint correlation coefficient takes the maximum value. The method can realize the acquisition of elevation information of the single-track multi-angle SAR target, and can be applied to the detailed investigation, mapping and the like of military targets.

Description

Multi-angle SAR elevation measurement method and system based on three-dimensional grid projection
Technical Field
The invention relates to a multi-angle SAR elevation measurement method based on three-dimensional grid projection, and belongs to the technical field of spaceborne synthetic aperture radar detection.
Background
The space-borne synthetic aperture radar has the characteristics of all-time and all-weather work, and is an effective means for space-to-ground observation. During a single transit period, the satellite-borne SAR system scans a target by using a beam azimuth, the scanning angle range can reach +/-45 degrees, the observation time can reach hundreds of seconds, and the method can be equivalent to the method of carrying out multi-azimuth observation on the target by using a three-dimensional curve antenna array so as to acquire three-dimensional geometric information of the target. The three-dimensional geometric information of the target obtained by multi-azimuth observation can be further used for super-resolution imaging and high-precision positioning of the target, fine description of the scene is realized, and the method has important application value.
For establishing a digital elevation model, analysis on imaging geometric characteristics of a multi-angle SAR image sequence shows that geometric registration errors are very sensitive to target elevation errors when an azimuth included angle between SAR images is large. Therefore, the two SAR images with larger azimuth included angles can be geometrically registered, and the assumed target elevation of the two SAR images which are accurately registered is used as the target elevation. And if the SAR image can be accurately judged whether to be registered, the target elevation can be accurately measured. The commonly used registration criterion in the actual measurement data processing is a coherence coefficient or a correlation coefficient between SAR images. Because there is no coherence between multi-azimuth SAR images, the correlation coefficient between SAR images is used as the registration criterion. However, when the azimuth included angle between the SAR images is large, the correlation between the images is low, and the registration accuracy is very poor by using the correlation coefficient as the registration criterion, so that the elevation measurement accuracy is very poor.
He et al, in the article "progress and prospect of curvilinear synthetic aperture radar three-dimensional imaging research" (article number: 2095-. However, the disadvantages of this method are: the method is realized by 3-dimensional FFT based on Fourier transform relation between echo data and scattering target coefficients, but the multi-angle SAR data is sparse in height dimension, and a fuzzy phenomenon exists after three-dimensional imaging is realized by Fourier transform. Kuangli et al propose in article "Multi-azimuth Multi-Baseline satellite-borne SAR three-dimensional imaging method research" (article number: 2095-. The method has the following defects: it requires multiple flights of information at a high cost.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the problem that high-precision elevation information cannot be obtained by utilizing phase information when the azimuth included angle between SAR images is large, a multi-angle SAR elevation measurement method based on three-dimensional grid projection is provided, and the real elevation of a target is extracted by utilizing a multi-azimuth observation projection relation.
The technical solution of the invention is as follows:
a multi-angle SAR elevation measurement method based on three-dimensional grid projection comprises the following steps:
(1) selecting a main image in a multi-angle SAR image sequence;
(2) searching a target elevation for each pixel in a main image to perform geometric registration on the multi-angle SAR image sequence, determining registration offset of each auxiliary image, and performing interpolation processing on each auxiliary image to obtain the multi-angle SAR image sequence after geometric registration;
(3) aiming at each search target elevation, calculating a joint correlation coefficient by using the multi-angle SAR image sequence obtained in the step (2) after geometric registration to obtain the change of the joint correlation coefficient along with the search target elevation;
(4) and selecting the search target elevation when the joint correlation coefficient takes the maximum value as the measured elevation of the target.
Further, the SAR image with the azimuth angle of 0 degree is selected as the main image for the multi-angle SAR image sequence.
Further, the step (2) searches for the elevation of the target for each pixel in the main image to perform geometric registration on the multi-angle SAR image sequence, and specifically comprises the following steps:
(2.1) dividing the main image pixels into reference lattice points and non-reference lattice points;
(2.2) solving the coordinates of a target point corresponding to the main image reference grid point on the auxiliary image through an iterative positioning process, namely forward positioning and reverse positioning;
(2.3) the coordinates of the target points corresponding to the non-reference grid points of the main image on the auxiliary image are solved by the following formula:
Figure BDA0002701679110000031
Figure BDA0002701679110000032
wherein (a) s,ref ,r s,ref ) Coordinates, delta a, of a target point corresponding to a reference grid point on the main image on the auxiliary image m For the increment of the azimuth coordinate of the non-reference grid point to be registered on the main image relative to the azimuth coordinate of the reference grid point, delta r m The increment of the distance coordinate of the non-reference grid point to be registered on the main image relative to the distance coordinate of the reference grid point is shown, delta h is the increment of the elevation of a target point corresponding to the non-reference grid point to be registered relative to the elevation of a target point corresponding to the reference grid point,
Figure BDA0002701679110000033
Figure BDA0002701679110000034
is a recurrence coefficient.
Further, the joint correlation coefficient is:
Figure BDA0002701679110000035
wherein (a, r) represents the pixel coordinates of the main image, h represents the elevation of the target, and M represents the multi-azimuth SAR
The number of images; ρ is a unit of a gradient m,m+1 Representing the correlation coefficient between the SAR images m and m + 1.
Further, the correlation coefficient between the SAR images is:
Figure BDA0002701679110000036
wherein，s i (l, k) and s j (l, k) represent the pixel amplitude values, μ, of the primary and secondary images, respectively, within the selected window i And mu j Respectively, the average value of the amplitudes of the pixels in the selected window of the main and auxiliary images, and (2L +1) × (2K +1) is the size of the selected window and has the unit of pixel.
Further, constructing a cost function h (a, r) to obtain target elevation information:
Figure BDA0002701679110000037
and obtaining the elevation information of the target by optimizing and solving the above formula.
Further, the present invention also provides an SAR elevation measurement system, including:
a main image selection module: selecting a main image in a multi-angle SAR image sequence;
a geometric registration module: searching a target elevation for each pixel in a main image to perform geometric registration on the multi-angle SAR image sequence, determining registration offset of each auxiliary image, and performing interpolation processing on each auxiliary image to obtain the multi-angle SAR image sequence after geometric registration;
a joint correlation calculation module: aiming at each search target elevation, calculating a joint correlation coefficient by using the acquired multi-angle SAR image sequence after geometric registration to obtain the change of the joint correlation coefficient along with the search target elevation;
A measurement elevation determination module: and selecting the search target elevation when the joint correlation coefficient takes the maximum value as the measured elevation of the target.
Compared with the prior art, the invention has the beneficial effects that:
(1) a target elevation measurement method based on single-track SAR recorded data is provided, and is suitable for a single-track multi-angle SAR system, and the system elevation information acquisition efficiency can be improved;
(2) the multi-angle SAR sequence image registration method is provided, images with large observation angles are accurately registered, and the problem of poor image registration accuracy caused by image decorrelation when the observation angles are large can be solved.
(3) And establishing a relation between the registration offset and the target elevation, and estimating the target elevation by using the offset between the images.
Drawings
FIG. 1 is a geometrical diagram of multi-azimuth observation of a satellite-borne SAR;
FIG. 2 is a schematic flow chart of a method for measuring a target elevation according to the present invention;
FIG. 3 is a schematic diagram of a two-dimensional grid of a main SAR image;
FIG. 4 is a schematic flow chart of a recursive formula based fast high-precision geometric registration process;
FIG. 5 is an illumination area diagram after interpolation processing is carried out on a DEM grid by adopting a fractal interpolation algorithm;
FIG. 6 is a simulated SAR image sequence, in which a-i are images at different azimuth angles;
FIG. 7 is a target elevation measurement;
FIG. 8 is a statistical histogram of target elevation measurement errors.
Detailed Description
The invention relates to the technical field of satellite-borne synthetic aperture radar detection, in particular to target elevation measurement of SAR multi-azimuth observation, which can be used for the situation that correlation between images is poor due to a large azimuth included angle between SAR images, target elevation precision elevation information cannot be obtained by utilizing SAR image phase information, and target elevation can be accurately measured by combining multi-angle SAR image sequences.
The final purpose of the invention is to extract the real elevation of the target by using the multi-azimuth observation projection relation. Aiming at the problem that high-precision elevation information cannot be obtained by utilizing phase information when the azimuth included angle between SAR images is large, a three-dimensional grid projection-based elevation measurement method is provided. The method selects a main image in a multi-angle SAR image sequence, searches for a target elevation in a three-dimensional grid, and geometrically registers other images and the main image. And calculating a joint correlation coefficient by using the geometric registration result of each search elevation to obtain the change of the joint correlation coefficient along with the search elevation. And selecting the search elevation with the maximum joint correlation coefficient value as the measured elevation of the target.
The multi-azimuth observation satellite-borne SAR system realizes long synthetic aperture observation of the same scene through beam azimuth scanning, and a data recording geometric schematic diagram of the system is shown in an attached figure 1.
All coordinates in FIG. 1 are established in the scene local coordinate system O-XYZ; the origin O of the coordinate system is positioned at a certain position in an observation scene, the direction pointed by the X axis is the ground distance direction, the Y axis points to the azimuth direction, and the Z axis points to the altitude direction; the satellite follows a curved orbit, from P 1 Continuously observing the ground scene until P 2 Stopping observation, and the velocity vectors of two satellites are respectively V 1 And V 2 ，θ 1 And theta 2 Is the included angle between two slope distance vectors and a velocity vector, and the observation azimuth span is
Figure BDA0002701679110000051
Assuming that the corresponding elevation of the scene reference plane is 0; a target position vector in the scene is a factory, the relative reference plane elevation is h, and the target is positioned to P 1 And P 2 Are respectively R 1 And R 2 . If the scene reference plane is taken as the imaging ground plane, P is aligned 1 Imaging the azimuth sub-aperture data, and setting the projection position of the target in the imaging plane as T 1 (ii) a To P 2 Imaging the azimuth sub-aperture data, and setting the projection position of the target in the imaging plane as T 2 。
Before the specific implementation steps are introduced, an SRTM DEM library mainly used in the method is simply introduced:
The SRTM data is mainly measured jointly by the United states space administration (NASA) and the national institute of defense mapping (NIMA). The acquired radar image data is processed for more than two years to form a digital terrain elevation model. DEM is a data set of plane coordinates (X, Y) and elevation (Z) of regular grid points within a certain range, and is mainly used for describing the spatial distribution of regional landform morphology.
Referring to fig. 2, the specific implementation steps of the invention are as follows:
step 1, selecting a main image, and generally selecting an SAR image with an azimuth angle of 0 degree as the main image for a multi-angle SAR image sequence;
step 2, searching a target elevation for each pixel in the main image, performing geometric registration on the multi-angle SAR image sequence, determining registration offset of each auxiliary image, and performing interpolation processing on each auxiliary image to obtain the multi-angle SAR image sequence after geometric registration; when the method is used for measuring the target elevation, registration is carried out on each pixel on the main SAR image and a plurality of SAR auxiliary images by adopting a geometric method on the assumption of different target elevations, and the calculation amount is very large. In the invention, a fast geometric registration method based on a recursion formula is used for replacing an iterative solution algorithm to improve the operation efficiency. With reference to figures 3 and 4 of the drawings,
The main image pixels are divided into reference grid points and non-reference grid points.
The coordinates of the target point corresponding to the main image reference grid point on the auxiliary image can be solved through an iterative positioning process, namely forward positioning and reverse positioning.
The coordinates of the target point corresponding to the non-reference grid point of the main image on the auxiliary image are solved by the following formula:
Figure BDA0002701679110000061
Figure BDA0002701679110000062
wherein (a) s，ref ，r s，ref ) Coordinates, delta a, of a target point corresponding to a reference grid point on the main image on the auxiliary image m For the increment of the azimuth coordinate of the non-reference grid point to be registered on the main image relative to the azimuth coordinate of the reference grid point, delta r m The increment of the distance coordinate of the non-reference grid point to be registered on the main image relative to the distance coordinate of the reference grid point is shown, delta h is the increment of the elevation of a target point corresponding to the non-reference grid point to be registered relative to the elevation of a target point corresponding to the reference grid point,
Figure BDA0002701679110000063
Figure BDA0002701679110000071
is a recurrence coefficient.
Step 3, aiming at each search target elevation, calculating a joint correlation coefficient by using the multi-angle SAR image sequence obtained in the step 2 after geometric registration to obtain the change of the joint correlation coefficient along with the search target elevation; the joint correlation coefficient is defined as follows:
Figure BDA0002701679110000072
wherein (a, r) represents the pixel coordinates of the main image, h represents the target elevation, and M represents the number of multi-azimuth SAR images. Rho m，m+1 Representing the correlation coefficient between SAR images m and m + 1.
The correlation coefficient is defined as follows:
Figure BDA0002701679110000073
wherein s is i (l, k) and s j (l, k) represent the pixel amplitude values, μ, of the primary and secondary images, respectively, within the selected window i And mu j Respectively, the average value of the amplitudes of the pixels in the selected window of the main and auxiliary images, and (2L +1) × (2K +1) is the size of the selected window and has the unit of pixel.
The correlation coefficient is calculated by using a plurality of windows of different sizes (e.g., windows of 5 × 5 and 11 × 11), and then adding the plurality of calculation results, the influence of the side lobe can be reduced. The influence of the SAR image speckle on the elevation measurement precision can be reduced through speckle filtering. The elevation measurement method combines two characteristics of high correlation between small azimuth angle SAR images and sensitivity of geometric registration errors between large azimuth angle SAR images to elevation errors, thereby ensuring the accuracy of height measurement.
And 4, selecting the search target elevation when the combined correlation coefficient takes the maximum value as the measurement elevation of the target. And constructing a cost function h (a, r) to convert the elevation measurement problem into an optimization problem. The calculation formula for measuring the elevation is as follows:
Figure BDA0002701679110000074
solving the above equation, and selecting h when JC takes the maximum value as the estimated elevation of the target.
The effect of the present invention will be further explained by combining the simulation experiment
Simulation conditions are as follows:
the accuracy of the elevation measurement method was verified using the simulation data with reference to the simulation parameters shown in table 1.
29 SAR images are simulated, the imaging Doppler frequency is uniformly distributed between-280000 Hz and 280000Hz, and the corresponding SAR image azimuth angles are distributed between-43.05 degrees and 43.05 degrees. The DEM used for simulating the SAR image is obtained in an SRTM DEM library, the grid spacing of the DEM is large, interpolation processing is carried out on the DEM by adopting a fractal interpolation algorithm, and the DEM after interpolation is projected to a main image (the SAR image with the azimuth angle of 0 degree) slant plane as shown in the attached figure 5. The ground object types are assumed to be soil and rock, the backscattering coefficient is obtained by calculation according to an Ulaby model, and the polarization mode is HH polarization.
TABLE 1 simulation parameters
Parameter(s) Parameter value
Radar carrier frequency 9.65GHz
Height of track 780km
Satellite velocity 7687m/s
Pulse sampling frequency 180MHz
Pulse repetition frequency 10000Hz
Center slope of scene 1161km
SAR image azimuth -43.05°～43.05°
Accuracy of measuring height 3m
Simulation result
The simulated SAR image is shown in fig. 6. As can be seen from fig. 6, the amplitude change between the images of the multi-angle SAR image sequence obtained by simulation increases, the geometric deformation change between the images increases, and the correlation between the images decreases as the azimuth angle between the images increases.
The experiment simulates the measurement of the target elevation of 29 SAR images. Since the current SRTM DEM has the elevation precision of 20m, 20m of elevation error is added to the DEM used in the simulation as a priori DEM. The elevation search range is-25 m to 25m of the prior DEM elevation superposition, and the elevation search interval is 0.1 m. When the geometrical registration is carried out by using a fast high-precision geometrical registration algorithm based on a recursion formula, the pixel interval of the reference grid is selected to be 20 multiplied by 20 pixels. FIG. 7 shows the target elevation measurements, and FIG. 8 shows the statistical histogram of the target elevation measurement errors. The target elevation measurement precision of the elevation measurement method based on three-dimensional grid projection is 2.67m and has higher elevation measurement precision by counting the root mean square value of the target elevation measurement error.
Those skilled in the art will appreciate that the invention may be practiced without these specific details.

Claims (8)

1. A multi-angle SAR elevation measurement method based on three-dimensional grid projection is characterized by comprising the following steps:
(1) selecting a main image in a multi-angle SAR image sequence;
(2) searching a target elevation for each pixel in a main image to perform geometric registration on the multi-angle SAR image sequence, determining registration offset of each auxiliary image, and performing interpolation processing on each auxiliary image to obtain the multi-angle SAR image sequence after geometric registration; the method specifically comprises the following steps:
(2.1) dividing the main image pixels into reference lattice points and non-reference lattice points;
(2.2) solving the coordinates of a target point corresponding to the main image reference grid point on the auxiliary image through an iterative positioning process, namely forward positioning and reverse positioning;
(2.3) the coordinates of the target points corresponding to the non-reference grid points of the main image on the auxiliary image are solved by the following formula:
Figure FDA0003602177780000011
Figure FDA0003602177780000012
wherein (a) s，ref ，r s，ref ) Coordinates, delta a, of a target point corresponding to a reference grid point on the main image on the auxiliary image m For the increment of the azimuth coordinate of the non-reference grid point to be registered on the main image relative to the azimuth coordinate of the reference grid point, delta r m The increment of the distance coordinate of the non-reference grid point to be registered on the main image relative to the distance coordinate of the reference grid point is shown, delta h is the increment of the elevation of a target point corresponding to the non-reference grid point to be registered relative to the elevation of a target point corresponding to the reference grid point,
Figure FDA0003602177780000013
is a recurrence coefficient;
(3) aiming at each search target elevation, calculating a joint correlation coefficient by using the multi-angle SAR image sequence obtained in the step (2) after geometric registration to obtain the change of the joint correlation coefficient along with the search target elevation;
(4) and selecting the search target elevation when the joint correlation coefficient takes the maximum value as the measured elevation of the target.
2. The multi-angle SAR elevation measurement method based on three-dimensional grid projection according to claim 1, characterized in that: and selecting the SAR image with the azimuth angle of 0 degrees as the main image for the multi-angle SAR image sequence.
3. The multi-angle SAR elevation measurement method based on three-dimensional grid projection according to claim 1, characterized in that: the joint correlation coefficient is:
Figure FDA0003602177780000021
wherein (a, r) represents the pixel coordinates of the main image, h represents the target elevation, and M represents the number of multi-azimuth SAR images; rho m，m+1 Representing the correlation coefficient between the SAR images m and m + 1.
4. The multi-angle SAR elevation measurement method based on three-dimensional grid projection as claimed in claim 3, characterized in that: the correlation coefficient between SAR images is:
Figure FDA0003602177780000022
wherein s is i (l, k) and s j (l, k) represent the pixel amplitude values, μ, of the primary and secondary images, respectively, within the selected window i And mu j Respectively, the average value of the amplitudes of the pixels in the selected window of the main and auxiliary images, and (2L +1) × (2K +1) is the size of the selected window and has the unit of pixel.
5. The multi-angle SAR elevation measurement method based on three-dimensional grid projection as claimed in claim 3, characterized in that: constructing a cost function h (a, r) to obtain target elevation information:
Figure 1
And obtaining the information of the elevation of the target by optimizing and solving the above formula.
6. The SAR elevation measurement system realized by the multi-angle SAR elevation measurement method based on three-dimensional grid projection as claimed in claim 1 is characterized by comprising:
a main image selection module: selecting a main image in a multi-angle SAR image sequence;
a geometric registration module: searching a target elevation for each pixel in a main image to perform geometric registration on the multi-angle SAR image sequence, determining registration offset of each auxiliary image, and performing interpolation processing on each auxiliary image to obtain the multi-angle SAR image sequence after geometric registration;
the method specifically comprises the following steps:
(2.1) dividing the main image pixels into reference grid points and non-reference grid points;
(2.2) solving the coordinates of a target point corresponding to the main image reference grid point on the auxiliary image through an iterative positioning process, namely forward positioning and reverse positioning;
(2.3) the coordinates of the target points corresponding to the non-reference grid points of the main image on the auxiliary image are solved by the following formula:
Figure FDA0003602177780000031
Figure FDA0003602177780000032
wherein (a) s，ref ，r s，ref ) Coordinates, delta a, of a target point corresponding to a reference grid point on the main image on the auxiliary image m For the increment of the azimuth coordinate of the non-reference grid point to be registered on the main image relative to the azimuth coordinate of the reference grid point, delta r m The increment of the distance coordinate of the non-reference grid point to be registered on the main image relative to the distance coordinate of the reference grid point is shown, delta h is the increment of the elevation of a target point corresponding to the non-reference grid point to be registered relative to the elevation of a target point corresponding to the reference grid point,
Figure FDA0003602177780000033
is a recurrence coefficient;
a joint correlation calculation module: aiming at each search target elevation, calculating a joint correlation coefficient by using the acquired multi-angle SAR image sequence after geometric registration to obtain the change of the joint correlation coefficient along with the search target elevation;
a measurement elevation determination module: and selecting the search target elevation when the joint correlation coefficient takes the maximum value as the measured elevation of the target.
7. The SAR elevation measurement system of claim 6, wherein: and selecting the SAR image with the azimuth angle of 0 degrees as the main image for the multi-angle SAR image sequence.
8. The SAR elevation measurement system of claim 6, wherein: the joint correlation coefficient is:
Figure FDA0003602177780000034
wherein (a, r) represents the pixel coordinates of the main image, h represents the target elevation, and M represents the number of multi-azimuth SAR images; rho m，m+1 Representing a correlation coefficient between the SAR images m and m + 1;
the correlation coefficient between SAR images is:
Figure FDA0003602177780000041
wherein s is i (l, k) and s j (l, k) represent the pixel amplitude values, μ, of the primary and secondary images, respectively, within the selected window i And mu j Respectively representing the average value of the amplitudes of the pixels in the selected window of the main and auxiliary images, wherein (2L +1) × (2K +1) is the size of the selected window and the unit is the pixel;
constructing a cost function h (a, r) to obtain target elevation information:
Figure 2
and obtaining the elevation information of the target by optimizing and solving the above formula.
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