CN116930965A - Chromatographic SAR three-dimensional imaging method of low-height platform - Google Patents
Chromatographic SAR three-dimensional imaging method of low-height platform Download PDFInfo
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Abstract
The invention discloses a chromatography SAR three-dimensional imaging method of a low-height platform, which comprises the following steps: acquiring SAR images; sparse inversion is carried out on SAR images in a lower view angle constraint range based on a cylindrical wave TomoSAR imaging model, and a scattering coefficient of a scattering body signal in a pixel along a high Cheng Xiang is determined; calculating lower view angle parameters according to the scattering coefficients; generating position coordinates of the scattering body in a ground coordinate system based on the lower visual angle parameters; according to the invention, sparse inversion is performed by constructing the cylindrical wave TomoSAR imaging model, so that the geometric deformation of a scatterer can be corrected, the three-dimensional imaging precision of the scatterer can be greatly improved, and meanwhile, the elevation search range is adaptively determined based on the height constraint, thereby realizing Gao Chengjie blurring and further improving the imaging precision.
Description
Technical Field
The invention belongs to the technical field of chromatographic SAR three-dimensional imaging, and particularly relates to a chromatographic SAR three-dimensional imaging method of a low-height platform.
Background
The tomoSAR imaging technology is that scattering signals of different heights in an elevation direction (perpendicular to a plane in the azimuth direction and a plane in the distance direction) can be inverted through multiple observations of the same target ground object, so that a real SAR imaging three-dimensional scene is restored. The TomoSAR imaging requires multiple baseline data, and advances slowly in the beginning of development due to limitations in factors such as small baseline numbers, track instability, etc. With the continuous maturation of the space-borne and airborne SAR systems, high-quality multi-baseline SAR images are successfully acquired, so that the reconstruction of the ground object height structure by the TomoSAR technology is possible, and further three-dimensional imaging is realized.
The tomoSAR imaging technology has remarkable advantages in reducing the three-dimensional structure of a building due to the unique elevation direction imaging capability. The TomoSAR can reconstruct a scattering section in a single pixel along an elevation direction, extract elevation position and intensity information of each scattering body, and further restore a three-dimensional structure of the whole building and obtain a high-precision three-dimensional city model in a scene range.
In recent years, many high-resolution SAR data have been obtained from low altitude platforms such as low altitude airplanes or drones, with flying heights of only a few kilometers or even hundreds of meters. Compared with a satellite-borne platform and the like, the SAR of the low-altitude platform has resolution advantages, but at the same time, the slant range (the distance from an SAR antenna to a ground object) of SAR data of the low-altitude platform is smaller, which can lead to reduction of the maximum non-fuzzy height, even approaches to the height of a scene building, and the height fuzzy which is difficult to filter is generated. Elevation blurring of TomoSAR becomes an important issue affecting three-dimensional imaging of buildings. Meanwhile, the flight height of the low-height platform causes that the plane wave assumption of the original TomoSAR imaging model is not applicable any more, and a certain geometric deformation can be caused to the three-dimensional imaging result.
Disclosure of Invention
The invention aims to provide a chromatographic SAR three-dimensional imaging method with a low-height platform, which aims to solve the problems of elevation blurring and geometric deformation of a three-dimensional imaging result.
The invention adopts the following technical scheme: a chromatography SAR three-dimensional imaging method of a low-height platform comprises the following steps:
acquiring SAR images;
sparse inversion is carried out on SAR images in a lower view angle constraint range based on a cylindrical wave TomoSAR imaging model, and a scattering coefficient of a scattering body signal in a pixel along a high Cheng Xiang is determined;
calculating lower view angle parameters according to the scattering coefficients;
position coordinates of the diffuser in a ground coordinate system are generated based on the lower viewing angle parameters.
Further, the cylindrical wave TomoSAR imaging model is:
wherein g n For the pixel values of the image formed by the nth antenna element, θ' =θ - θ 0 θ is the downward viewing angle of the diffuser, θ 0 For the downward viewing angle of the reference point, the reference point is the ground point with the smallest slant distance in the detection area, the constraint range denoted by delta theta ', r is the slant distance of the scatterer, gamma (rθ') denotes the scattering coefficient, ζ, along a height Cheng Xiang of the signal of the scatterer with a tilt r and a lower viewing angle parameter θ n For the elevation frequency of the nth antenna element epsilon n Is the image noise of the nth antenna element.
Further, the generation method of the lower visual angle constraint range comprises the following steps:
determining building maximum height threshold h in detection area 1 And a minimum height threshold h 2 ；
According to the maximum height threshold h 1 And a minimum height threshold h 2 The method comprises the steps of carrying out a first treatment on the surface of the Calculating the upper bound and the lower bound of the self-adaptive elevation search range;
a lower viewing angle constraint range is generated from the upper and lower bounds.
Further, before determining the scattering coefficient of the signal of the scatterer in the pixel along the high Cheng Xiang, further comprises:
and performing scatterer detection on the TomoSAR image.
Further, a three-threshold method is adopted to detect scatterers of the SAR image;
wherein the three thresholds include a coherence coefficient threshold, an average amplitude threshold, and an amplitude dispersion index threshold.
Further, the target problem when sparse inversion is performed on the SAR image is:
wherein, gamma is the set of all scattering coefficients, G is the set of pixel values of the image formed by N antenna array elements, G is the observation matrix, N is the total number of antenna array elements,is the standard deviation of the SAR image observation noise epsilon.
Further, generating location coordinates of the diffuser in the ground coordinate system based on the under-view parameters includes:
Y P ＝k·Xbin，
X P ＝r i ·sin(θ 0 +θ′ P )-X，
Z P ＝-r i ·cos(θ 0 +θ′ P )+H，
wherein X is P 、Y P And Z P Respectively three-axis coordinates of the scatterer P in a ground coordinate system, k represents the column number of the azimuth direction of the scatterer P in the SAR image, xbin is the azimuth resolution, and theta' P For the lower viewing angle parameter of the diffuser P, X is the X-axis coordinate value of the reference point, r i And H is the height from the phase center of the SAR antenna to the ground.
Further, the objective problem is solved by adopting an OMP greedy algorithm, a basis pursuit algorithm or an atomic norm minimization algorithm.
Further, generating the lower viewing angle constraint range from the upper and lower bounds includes:
Δθ′ i ＝[s′ i min /r i ，s′ i max /r i ]，
wherein, delta theta' i For the i-th distance inward lower viewing angle constraint range, s' i min For the ith distance to the corresponding lower bound, s' i max For the ith distance to the corresponding upper bound, r i Is the slant distance of the scatterer in the ith column of pixels of the SAR image range direction.
In another aspect of the present invention, a low-height-platform tomographic SAR three-dimensional imaging apparatus includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.
The beneficial effects of the invention are as follows: according to the invention, sparse inversion is performed by constructing the cylindrical wave TomoSAR imaging model, so that the geometric deformation of a scatterer can be corrected, the three-dimensional imaging precision of the scatterer can be greatly improved, and meanwhile, the elevation search range is adaptively determined based on the height constraint, thereby realizing Gao Chengjie blurring and further improving the imaging precision.
Drawings
FIG. 1 is a geometric schematic of TomoSAR three-dimensional imaging in an embodiment of the present invention;
fig. 2 is a schematic diagram of a coherence coefficient distribution of a TomoSAR image before and after preprocessing in an embodiment of the present invention;
FIG. 3 is a schematic diagram showing the calculation results of the boundary of the region Δθ' in each pixel according to the embodiment of the present invention;
FIG. 4 is a graph showing the estimation result of the number of scatterers of each pixel according to the embodiment of the present invention;
FIG. 5 is a schematic diagram of inversion results of the scattering coefficient γ according to an embodiment of the present invention;
FIG. 6 is a graph of amplitude and Google Earth optics for data in an embodiment of the present invention;
FIG. 7 is a side view of the result of a three-dimensional point cloud implementation in an embodiment of the invention;
fig. 8 is a front view comparison diagram of three-dimensional point cloud data obtained by the method and the prior art.
Detailed Description
The invention will be described in detail below with reference to the drawings and the detailed description.
The existing general method for realizing TomoSAR three-dimensional imaging is based on a scattering model of plane waves. The imaging steps can be summarized as follows: (1) Selecting a proper elevation search range, and ensuring that all buildings in the scene are covered in the three-dimensional imaging boundary; (2) Inverting the elevation backscatter signal by a super-resolution iterative algorithm, such as an orthogonal matching pursuit combined with bayesian information criterion algorithm (OMP-BIC); (3) Calculating the position of the scattering body in the elevation direction by detecting the peak value of the scattering signal; and (4) obtaining a three-dimensional imaging result through coordinate transformation.
The plane wave scattering model assumes that the detected signal arriving at the imaging scene is a plane wave and inverts the scatterer signal at high Cheng Xiangshang. OMP-BIC is an elevation sparse inversion algorithm, and is divided into OMP and BIC. The OMP algorithm, namely the orthogonal matching pursuit algorithm, is a compressed sensing algorithm with higher calculation efficiency, is commonly used for sparse signal estimation, and can inhibit blurring to a certain extent on the side lobe suppression and super-resolution performance due to the traditional spectrum estimation algorithm. But OMP algorithms require sparsity as an input, so BIC algorithms are required to estimate sparsity. In TomoSAR, sparsity is equal to the number of scatterers, so OMP-BIC algorithms are often used for elevation-wise sparse inversion of TomoSAR.
In the tomoSAR imaging, although the OMP-BIC algorithm has a certain super-resolution advantage compared with the traditional spectrum estimation algorithm, the method can not distinguish the fuzzy number of the tomoSAR elevation direction, the elevation fuzzy problem can still be remained, meanwhile, the BIC algorithm has insufficient precision in the aspect of estimating the number of scatterers, noise can be generated, and improvement is needed. In addition, in the TomoSAR application of the low-altitude SAR platform, the adopted scattering model based on plane waves cannot solve the problem of geometric deformation, and has limited filtering effect on the problem of elevation ambiguity of the TomoSAR imaging of the low-altitude SAR platform.
Aiming at the problems of elevation direction blurring and geometric deformation of the low-altitude platform TomoSAR imaging, the existing TomoSAR imaging method is insufficient in performance in Gao Chengjie blurring, geometric deformation correction is not considered, and the estimation accuracy of the number of scatterers is low.
The invention utilizes the imaging geometric characteristics of a low-height SAR platform, proposes a TomoSAR imaging model based on a cylindrical wave hypothesis to correct geometric deformation, adopts a height constraint as a geometric constraint of a solution space to realize Gao Chengjie blurring, and proposes a refined scatterer pre-estimation method to improve the estimation precision of the number of scatterers.
In the embodiment of the present invention, an airborne SAR system is taken as an example, and as shown in fig. 1, an application scenario diagram is shown. In the figure, an airplane flies from one end to the other end of a region to be detected in the left side of the region to be detected, an image is acquired, and a shadow region is a ground region corresponding to a radar detection region. The forward direction of the aircraft is the azimuth direction; the plane forms a line with a projection point on the ground, forms another line with a certain position point of the detection area, and the included angle of the two lines is the lower visual angle; the airborne SAR faces to a position point in the detection area to be in a distance direction, namely a radar sight line direction, and the distance direction is in a vertical direction; the projection point of the plane on the ground and the position point of the detection area form a ground distance direction; the distance direction and the azimuth direction form a plane, and the direction perpendicular to the plane and facing the sky is the elevation direction.
Specifically, the invention discloses a low-height platform chromatographic SAR three-dimensional imaging method, which comprises the following steps: acquiring SAR images; sparse inversion is carried out on SAR images in a lower view angle constraint range based on a cylindrical wave TomoSAR imaging model, and a scattering coefficient of a scattering body signal in a pixel along a high Cheng Xiang is determined; calculating lower view angle parameters according to the scattering coefficients; position coordinates of the diffuser in a ground coordinate system are generated based on the lower viewing angle parameters.
According to the invention, sparse inversion is performed by constructing the cylindrical wave TomoSAR imaging model, so that the geometric deformation of a scatterer can be corrected, the three-dimensional imaging precision of the scatterer can be greatly improved, and meanwhile, the elevation search range is adaptively determined based on the height constraint, thereby realizing Gao Chengjie blurring and further improving the imaging precision.
The above-mentioned scatterers refer to buildings in the detection area, such as high buildings, high towers, etc., and may of course also include some rockets, ground, etc.
In one embodiment, the SAR dataset (i.e., SAR image) is preprocessed prior to sparse inversion. The purpose of the preprocessing is to enhance the coherence between the SAR main image and other images in the SAR image set, including image registration, amplitude and phase error correction, etc. The SAR main image is one SAR image selected from the image set.
Specifically, the coherence coefficient of each pixel of the TomoSAR image before and after preprocessing is calculated, and the pixel number distribution of the coherence coefficient is obtained, as shown in fig. 2, which is the coherence coefficient distribution of the TomoSAR image before and after preprocessing. From the figure, it can be seen that the preprocessing operation improves the coherence coefficient of the TomoSAR image, and lays a foundation for subsequent three-dimensional imaging.
For low-altitude platform SAR systems, the radar microwaves actually reaching the target are more similar to cylindrical waves, and the signal wave fronts are coaxial cylindrical surfaces. The echo signal can be regarded as a circular wave extending in azimuth in the range-elevation plane. Therefore, when the distance between the SAR antenna phase center (Antenna Phase Center, APC) and the target is reduced, the error caused by the plane wave model is not negligible and needs to be corrected. The present invention thus proposes a general model of TomoSAR imaging based on the cylindrical wave hypothesis:
wherein g n For the pixel values of the image formed by the nth antenna element, S '(θ) represents the mapping of the lower viewing angle to the correction elevation direction S',is the first derivative of S' (θ). Unlike tomosynthesis SAR imaging based on a plane wave model, the scattering coefficient in the cylindrical wave model is integrated along the lower viewing angle, rather than along the elevation direction s. The corrected elevation direction is a correction of the elevation direction that approximates but does not coincide with the elevation direction.
Let the direction along the cylindrical wavefront be the correction elevation direction, and the mapping relationship between the downward viewing angle and the correction elevation direction be s' = (θ - θ) 0 )r＝θ′ r The above formula can then be further expressed as:
wherein, since all scatterers in one pixel have the same slant distance, the scatterersThe injection profile is an arc with the main APC position as the center of the circle. θ' =θ - θ 0 θ is the downward viewing angle of the diffuser, θ 0 For the downview of the reference point, the reference point is the ground point with the smallest slope distance in the detection area, delta theta ' represents the constraint range of theta ', r is the slope distance of the scatterer, gamma (rtheta ') represents the scattering coefficient of the signal of the scatterer with the slope distance r and the downview parameter theta ' along the high Cheng Xiang, and delta theta ' represents the constraint range of theta n For the elevation frequency of the nth antenna element epsilon n Image noise for the nth antenna element, where j represents the imaginary part of the complex number.
In addition, in one embodiment of the invention, an adaptive method for determining the altitude searching range based on altitude constraint is adopted. In order to accurately invert the scatter signal, it is necessary to find a suitable expression based on the modified elevation search range. Assuming that the heights of urban buildings in the same scene are in the same order of magnitude level, and the elevation search range is generally determined by a proper elevation constraint, the invention provides an adaptive elevation search range determining method based on the elevation constraint.
Determining maximum height threshold and minimum height threshold h of buildings in detection area based on a priori information of buildings in imaging scene 2 As a height threshold pair. Then according to the maximum height threshold h 1 And a minimum height threshold h 2 The method comprises the steps of carrying out a first treatment on the surface of the Calculating the upper bound and the lower bound of the self-adaptive elevation search range; finally, generating the lower visual angle constraint range according to the upper bound and the lower bound
Wherein, get h 0 =0 is ground height, h 1 The roof height of the highest building can be taken. Since the ground scatter information is also contained in the SAR echo, it is necessary to provide a redundancy value to the three-dimensional inversion of the ground scatterer, so h 2 Can take the ground height value h 0 One empirical value is as follows.
From the geometry of the TomoSAR imaging, it is possible to obtain:
the boundaries (upper and lower) of the adaptive elevation search range based on the elevation threshold constraint are then:
from the above, Δs' i ＝[s′ i min ，s′ i max ]Then the elevation search range of all pixels within the ith distance can be obtained with a lower viewing angle constraint range of Δθ' i ＝[s′ i min /r i ，s′ i max /r i ]. Wherein, delta theta' i For the i-th distance inward lower viewing angle constraint range, s' i min For the ith distance to the corresponding lower bound, s' i max For the ith distance to the corresponding upper bound, r i Is the slant distance of the scatterer in the ith column of pixels of the SAR image range direction.
Specifically, as shown in fig. 3, a schematic diagram of the calculation result at each pixel (expressed in radians) is shown for the boundary of the section Δθ ', fig. 3 (a) is a graph of the calculation result for the upper boundary of the section Δθ ', and fig. 3 (b) is a graph of the calculation result for the lower boundary of the section Δθ '.
In one embodiment, determining the scattering coefficient of the signal of the scatterer in the pixel along the high Cheng Xiang further comprises: and detecting a scatterer of the TomoSAR image. The three thresholds in this embodiment include a coherence coefficient threshold, an average amplitude threshold, and an amplitude dispersion index threshold.
Firstly, SAR image scatterer detection is carried out, and scatterers are often extracted by setting a threshold value of a decision variable. The invention adopts three-threshold scatterer detection, and sets a small threshold related to the coherence coefficient and the signal-to-noise ratio according to different data sets so as to remove seriously decohered scatterers. The three thresholds are the coherence coefficient, the average amplitude and the amplitude dispersion index, respectively. The three threshold detection steps are as follows. First, pixels of the entire region are filtered by the coherence coefficient and average amplitude detection. The result of the coherence factor detection is then further filtered by amplitude dispersion index detection. Finally, the lost pixels in the last step are compensated through the result of the amplitude average value detection. The result of the three-threshold detection can be expressed as:
therein, P, P γ 、And->The remaining pixels after detection of the three thresholds, the coherence coefficient, the average amplitude and the amplitude dispersion index, respectively. After this step, most of the pixels are discarded as non-scatterers.
As shown in fig. 4, a graph of the estimated number of scatterers per pixel in an embodiment of the present invention shows the number of scatterers per pixel. The pixel with the number of scatterers of 0 is a non-scatterer pixel. There are at most 3 scatterers in a pixel.
The pre-classification of scatterers based on average amplitude is then performed, i.e. whether a double or triple scatterer is within a pixel is determined by a set threshold value that is a multiple of the average amplitude of the image. There are few pixels in the SAR image that exceed three scatterers, so the number of scatterers greater than three is not considered.
In an embodiment of the present invention, the TomoSAR model (i.e., the target problem) based on the cylindrical wave hypothesis can be solved by applying a sparse constraint (e.g., L0 norm regularization):
wherein, gamma is the set of all scattering coefficients, G is the set of pixel values of the image formed by N antenna array elements, G is the observation matrix, N is the total number of antenna array elements,is the standard deviation of the SAR image observation noise epsilon.
The objective problem is then solved using OMP greedy algorithm, basis tracking algorithm, or atomic norm minimization algorithm. Using a greedy algorithm such as OMP to solve equation (9), the sparsity (i.e., the number of scatterers) is required as an input, and finally, the set γ is obtained as a set of all scattering coefficients, and is converted into a corresponding lower viewing angle parameter θ'.
Taking the inversion result of the scattering coefficient gamma of a certain pixel as an example, the result is shown in fig. 5, and it can be seen from the graph that the inversion scattering coefficient peak position is corrected by the method under the constraint of the self-adaptive search range.
Finally, assume that the distance-bearing pixel (i, k) contains a scatterer P. The position of the scattering point P in the corrected elevation direction is s' P The lower viewing angle of the scattering point P is θ P . Taking the perpendicular point of APC on the ground as the origin of the ground coordinate system, the ground distance direction as the X axis and the azimuth direction as the Y axis, so that the Y coordinate of the scattering point P on the ground coordinate system can be obtained according to the SAR imaging geometrical relationship:
Y P ＝k·Xbin (8)
furthermore, the following relationship can be derived:
wherein, θ' P ＝θ P -θ 0 ＝s′ P /r i The X-coordinate and Z-coordinate of the scatterer P in the ground coordinate system are respectively:
X P ＝r i ·sin(θ 0 +θ′ P )-X (11)
Z P ＝-r i ·cos(θ 0 +θ′ P )+H (12)
and calculating the positions of all the scatterers of each pixel one by one under a ground coordinate system. Thus, a three-dimensional point cloud of the urban area of the large scene can be constructed. In the formulas (8) - (12), k represents the column number of the azimuth direction of the scatterer P in the SAR image, xbin is the azimuth resolution, θ' P For the lower viewing angle parameter of the diffuser P, X is the X-axis coordinate value of the reference point, r i And H is the height from the phase center of the SAR antenna to the ground.
Taking a published SAR data set of the Chinese academy in an Emei area as an example, 12 images are taken, the image size is 3600 multiplied by 1800, the flying height of the platform is about 1900m, and the characteristics of a low-height SAR platform are met. Fig. 6 (a) is an amplitude diagram of the employed data, and fig. 6 (b) is a *** earth optical diagram. Fig. 7 shows a side view of the implementation result of the three-dimensional point cloud of the present invention, fig. 7 (a) is an elevation blur image in the TomoSAR three-dimensional point cloud, fig. 7 (b) is a side view of the three-dimensional point cloud of the prior method (imaging model based on plane wave assumption), and fig. 7 (c) is a side view of the three-dimensional point cloud of the method (cylindrical wave model+height constraint+improved scatterer pre-estimation) proposed by the present invention. Fig. 8 (a) is a three-dimensional point cloud elevation view of a prior art method (imaging model based on plane wave assumption), and fig. 8 (b) is a three-dimensional point cloud elevation view of the inventive method (cylindrical wave model + height constraint + improved scatterer pre-estimation).
From the above, although the existing method can realize TomoSAR three-dimensional imaging, there are still some elevation blurs and noise points, and there is a curved deformation of the point cloud. Compared with the existing method, the method provided by the invention has the advantages that the elevation blurring and noise points are obviously reduced, the building is clearer, and the deformation correction is effectively realized. The three-dimensional point cloud obtained by the prior method has partial artifacts, such as an elliptical frame area in fig. 8 (a), and the method provided by the invention suppresses the artifacts. Meanwhile, the heights of the ground points in the three-dimensional point cloud obtained by the prior method are uneven, the heights of the ground points at the scene edge are low, and certain deformation distortion exists, as shown in a rectangular frame area in fig. 8 (a); the method of the present invention reduces deformation distortion, such as the rectangular frame area of fig. 8 (b).
In summary, the invention modifies the TomoSAR imaging model based on plane wave hypothesis into the model based on cylindrical wave hypothesis, which is helpful for geometric deformation correction of three-dimensional imaging. An adaptive determination of an elevation search range based on altitude constraint is provided, and elevation blurring is filtered. The method for pre-estimating the fine scatterers is adopted, and three-threshold estimation is utilized, so that the pre-estimation precision of the number of the scatterers is improved, and the imaging noise is reduced.
According to the invention, a low-altitude platform TomoSAR (namely an airborne platform and an unmanned aerial vehicle platform) three-dimensional imaging is researched, the influence of near-field conditions in TomoSAR imaging and elevation blurring on imaging is considered, a TomoSAR imaging model based on cylindrical waves is provided, a method for adaptively determining an elevation search range based on altitude constraint is provided, a refined scatterer pre-estimation method is adopted, and finally an OMP sparse inversion algorithm and three-dimensional positioning of a scatterer under a ground coordinate system are utilized, so that three-dimensional imaging of a multi-building scene is completed.
Compared with the prior art, the method solves the problems of elevation blurring and geometric deformation of the TomoSAR imaging of the low-altitude platform. The invention realizes Gao Chengjie blurring under the condition that the elevation blurring position of the data is very close to the building height, and reduces noise points. The invention improves the geometric deformation phenomenon and the accuracy of the three-dimensional point cloud. The invention conforms to the trend of the time of rapid development of the low-height SAR platform and has wide application prospect in the research of the low-height SAR platform.
Claims (10)
1. The chromatography SAR three-dimensional imaging method of the low-height platform is characterized by comprising the following steps of:
acquiring SAR images;
sparse inversion is carried out on the SAR image in a lower view angle constraint range based on a cylindrical wave TomoSAR imaging model, and a scattering coefficient of a signal of a scatterer in a pixel along a high Cheng Xiang is determined;
calculating lower view angle parameters according to the scattering coefficients;
and generating position coordinates of the scattering body in a ground coordinate system based on the lower view angle parameters.
2. The low-altitude platform tomosynthesis SAR three-dimensional imaging method according to claim 1, wherein the cylindrical wave TomoSAR imaging model is:
wherein g n For the pixel values of the image formed by the nth antenna element, θ' =θ - θ 0 θ is the downward viewing angle of the diffuser, θ 0 For the downward viewing angle of the reference point, the reference point is the ground point with the smallest slant distance in the detection area, the constraint range denoted by delta theta ', r is the slant distance of the scatterer, gamma (rθ') denotes the scattering coefficient, ζ, along a height Cheng Xiang of the signal of the scatterer with a tilt r and a lower viewing angle parameter θ n For the elevation frequency of the nth antenna element epsilon n Is the image noise of the nth antenna element.
3. The low-altitude platform tomographic SAR three-dimensional imaging method according to claim 2, wherein said lower viewing angle constraint range is generated by:
determining building maximum height threshold h in detection area 1 And a minimum height threshold h 2 ；
According to the maximum height threshold h 1 And a minimum height threshold h 2 The method comprises the steps of carrying out a first treatment on the surface of the Calculating the upper bound and the lower bound of the self-adaptive elevation search range;
the lower viewing angle constraint range is generated from an upper bound and a lower bound.
4. A low-elevation platform tomosynthesis SAR three-dimensional imaging method according to claim 3, wherein before determining the scattering coefficient of the scatterer signal in the pixel along high Cheng Xiang, further comprising:
and detecting a scatterer of the SAR image.
5. The low-altitude platform tomographic SAR three-dimensional imaging method as set forth in claim 4, wherein said SAR image is subjected to scatterer detection by a three-threshold method;
wherein the three thresholds include a coherence coefficient threshold, an average amplitude threshold, and an amplitude dispersion index threshold.
6. A low-altitude platform tomographic SAR three-dimensional imaging method according to any one of claims 2-5, wherein the target problem when sparse inversion is performed on the SAR image is:
wherein, gamma is the set of all scattering coefficients, G is the set of pixel values of the image formed by N antenna array elements, G is the observation matrix, N is the total number of antenna array elements,is the standard deviation of the SAR image observation noise epsilon.
7. The low-elevation platform tomosynthesis SAR three-dimensional imaging method of claim 6, wherein generating the position coordinates of the scatterer in the ground coordinate system based on the lower viewing angle parameter comprises:
Y P ＝k·Xbin，
X P ＝r i ·sin(θ 0 +θ′ P )-X，
Z P ＝-r i ·cos(θ 0 +θ′ P )+H，
wherein X is P 、Y P And Z P Three-axis seating of scatterers P in ground coordinate systemThe index, k, represents the column number of the scatterer P in the azimuth direction in the SAR image, xbin is the azimuth resolution, θ '' P For the lower viewing angle parameter of the diffuser P, X is the X-axis coordinate value of the reference point, r i And H is the height from the phase center of the SAR antenna to the ground.
8. The low-altitude platform tomographic SAR three-dimensional imaging method according to claim 6, wherein OMP greedy algorithm, basis tracking algorithm or atomic norm minimization algorithm is used to solve the objective problem.
9. A low-altitude platform tomosynthesis SAR three-dimensional imaging method according to claim 3, wherein generating the lower viewing angle constraint range according to upper and lower bounds comprises:
Δθ′ i ＝[s′ imin /r i ，s′ imax /r i ]，
wherein, delta theta' i For the i-th distance inward lower viewing angle constraint range, s' imin For the ith distance to the corresponding lower bound, s' imax For the ith distance to the corresponding upper bound, r i Is the slant distance of the scatterer in the ith column of pixels of the SAR image range direction.
10. A low-height platform tomosynthesis SAR three-dimensional imaging apparatus comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 9 when executing the computer program.
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