CN113093184B - Interferometric measurement method based on video synthetic aperture radar - Google Patents
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Abstract
The invention belongs to the technical field of radar interferometry, and particularly relates to an interferometry method based on a video synthetic aperture radar. The method mainly comprises the following steps: firstly, a video SAR interferometric model is established according to a model of a traditional InSAR, and then a target elevation inversion formula is deduced according to the model. Secondly, according to the view angle change of the main image and the auxiliary image to be obtained in each sub-aperture in the video SAR, an SIFT registration algorithm is provided, and then the main image and the auxiliary image after registration are subjected to conjugate multiplication to obtain an interference image. And then phase unwrapping is carried out on the obtained interferogram, and the elevation information of the target is calculated according to an elevation inversion formula. And establishing a DEM of the target area according to the elevation information at the coordinate position, and correcting the DEM. And finally, combining all the steps to obtain the video SAR interferometry. The method provides a video SAR interferometric model and an elevation inversion formula of a bunching mode, and provides a specific method aiming at related steps.
Description
Technical Field
The invention belongs to the technical field of radar interferometry, and particularly relates to an interferometry method based on a video synthetic aperture radar.
Background
The Synthetic Aperture Radar (Interferometric Synthetic Aperture Radar, InSAR) technology benefits from the maturity and development of the Synthetic Aperture Radar (SAR) technology to cluster a high-precision earth observation technology. The InSAR technology is a space-to-ground observation technology and is a product combining the traditional SAR remote sensing technology with an interference technology. The three-dimensional information of the target area is obtained by carrying out interference processing on two coherent images of the same area, and the InSAR technology improves the microwave detection technology from a two-dimensional plane to a three-dimensional space. The InSAR is developed based on the SAR technology, has outstanding advantages of the SAR all-weather, high precision and large area, and has unique advantages in the aspects of earth surface observation, ground deformation monitoring, glacier movement, disaster early warning, engineering body (bridge, dam) deformation and the like. InSAR technology is becoming the most dominant means of earth observation.
With the advent and development of video SAR, research into interferometry using video SAR has attracted the attention of many scholars. The terahertz technology is applied to a video SAR system, so that the video SAR can observe a target area in real time in certain scenes. The video SAR obtains continuous frame images with high frame rate and high resolution by continuously irradiating the target area, the defect of low imaging efficiency in the traditional InSAR is overcome, and the combination of the interferometry technology and the unique advantages of the video SAR is one of prospective subjects for exploring the application prospect of the video SAR. The rapid acquisition of a high-precision Digital Elevation Model (DEM) by utilizing an InSAR technology is one of the main applications of the InSAR technology at present. The conventional InSAR technology is based on the stripe SAR, but the imaging mode of the video SAR is a bunching mode, and the conventional InSAR technology cannot be compatible with the video SAR, so that the conventional InSAR technology cannot be used for the interferometric measurement of the video SAR, and an interferometric measurement method suitable for the bunching SAR is urgently needed. Moreover, when the conventional InSAR technology cannot process target imaging, factors such as overlapping, shielding and the like can cause phase loss, so that the precision of a measurement result is reduced.
Disclosure of Invention
In order to solve the problems, the invention provides a video SAR interferometry method suitable for a beamforming mode. The method has the basic idea that a video SAR interferometric measurement model is provided by combining an imaging mode of a video SAR, a target elevation inversion formula is deduced, and an interferometric measurement process applicable to the video SAR is provided. Meanwhile, the method utilizes the advantage of continuous imaging of the video synthetic aperture radar, and can reduce the error of target elevation inversion. Firstly, a beam bunching mode interferometry model is established, and a target elevation inversion formula is deduced according to the interferometry model. And then, according to the imaging characteristics of the bunching mode, providing a main image registration method and an auxiliary image registration method, and then carrying out conjugate multiplication, land removing, filtering and unwrapping on the registered images to obtain the height information of each sub-aperture. And secondly, performing cross registration by using main and auxiliary images of adjacent sub-apertures, performing subsequent steps, and performing data screening and averaging on the height information generated for multiple times based on the sub-aperture where the main image is located to obtain a relatively accurate result.
The technical scheme of the invention is as follows: an interferometry method based on a video synthetic aperture radar is used for an airborne double-antenna interferometric SAR system and is characterized by comprising the following steps:
s1, establishing a coordinate system according to the imaging model of the video SAR and the vertical plane where the main antenna and the auxiliary antenna are located, establishing an interferometric model of the target in the video SAR bunching mode, and obtaining an inversion formula of the elevation information of the target:
where H is the height of the main antenna, O is the origin of the coordinate system, P' is the projection of the target P on the ground, R 1 The main antenna slant distance, alpha is the included angle between the base line and the horizontal plane, B is the distance between the main antenna and the auxiliary antenna, and the actual imaging positions of the target in the main and auxiliary images are respectively P 1 And P 2 ，P 1 (x 1 ,y 1 ,0)，P 2 (x 2 ,y 2 ,0)；
S2, interferometric measurement is carried out in an airborne double-antenna mode, two SAR images are obtained in each sub-aperture, and main and auxiliary SAR images in the sub-apertures are registered by utilizing an SIFT algorithm;
s3, performing conjugate multiplication on the main and auxiliary complex images generated after registration to obtain an interferogram of the target under the sub-aperture, wherein the phase in the interferogram represents the phase error caused by different distances between the antenna and the same target under different angles of view, and the relation between elevation information h and a phase difference delta phi is obtained:
wherein theta is an included angle between the main antenna and the target, and lambda represents the wavelength of the video synthetic aperture radar;
s4, performing phase unwrapping on the obtained interferogram by using a least square phase unwrapping method based on an error equation to obtain an unwrapped interference phase;
s5, elevation inversion: in phi ( 0 Indicates the interference phase offset, phi' indicates the interference phase after unwrapping, and the skew difference DeltaR is
The elevation value h of the corresponding ground target is as follows:
the height information of the target can be obtained through the phase information, and the video synthetic aperture radar interferometry is realized.
Further, the method also comprises the following steps:
s6, multi-aperture data fusion: suppose that the video SAR system obtains n groups of sample data of a target area as D 1 ,D 2 ,D 3 ,…,D n-1 ,D n For any coordinate (x, y) in the target area, there are n sets of elevation sample data H 1 ,H 2 ,H 3 ,…,H n-1 ,H n Screening the n groups of elevation sample data, and eliminating unreliable data to improve the measurement precision; assuming that the n groupsThe sample data obeys normal distribution, i.e. H to N (mu, sigma) 2 ) Given a confidence level of 0.9 and a significance level of α ═ 0.1, it is necessary to first determine a mean value e (h) of the elevation sample data as:
in the above formula, the first and second carbon atoms are,
represents the mean of the sample data, using S 2 Represents the variance d (h) of the elevation sample data, namely:
on the premise of assuming that the elevation sample data obeys normal distribution, a confidence interval with a confidence of 0.9 about H is obtained as follows:
after the confidence interval is obtained, the elevation sample data are screened according to the confidence interval, the sample data in the confidence interval are reserved, otherwise, the sample data are abandoned, and the m groups of elevation sample data obtained after screening are assumed to be h 1 ,h 2 ,h 3 ,…,h m-1 ,h m Calculating the mean value of the m groups of data
Averaging the obtained data
As at scene coordinates (x, y)And then calculating the elevation values of the rest coordinates in the scene to finally obtain the three-dimensional information corresponding to all the coordinates in the imaging scene.
The method has the advantages that the method provides a video SAR interferometric model of a bunching mode and an elevation inversion formula, and provides a specific method aiming at related steps.
Drawings
Fig. 1 is a model of video SAR interferometry.
Fig. 2 is a SIFT registration step suitable for video SAR interferometry.
Fig. 3 is an interferometric procedure of the video SAR.
Fig. 4 is a video SAR multi-aperture data fusion method.
Detailed Description
The invention is described in detail below with reference to the drawings.
The invention is suitable for the airborne double-antenna interference SAR system, mainly include:
according to the imaging characteristics of the video SAR, a bunching mode interferometric model is established, and an elevation inversion formula of a target is deduced.
And (3) establishing a video SAR interferometric model as shown in the attached figure 1. In FIG. 1, A 1 And A 2 Is the position of the main and auxiliary antennas in the kth sub-aperture, A 2 Is a secondary antenna A 2 And in projection on the ground, B is the distance between the two antennas, namely the length of the base line, and H is the height of the antenna 1. Alpha is the angle between the base line and the horizontal plane, R 1 And R 2 The slant distances from the two antennas to the target are respectively, P is the actual position of the target point, the height is h, P' is the projection of the target P on the ground, P 1 ' and P 2 ' are the actual imaging positions of the object P in the primary and secondary images, respectively. Using the known information of the above-mentioned positions, the main antenna a is calculated 1 And obtaining the actual height h of the target by the included angle theta between the target and the target.
Antenna A 1 The phase of (a) is expressed as:
antenna A 2 The phase of (a) is expressed as:
wherein f is c For the working carrier frequency, c is the speed of light, R 1 Is the main antenna slant distance, R 2 For the secondary antenna slant, the phase difference Δ φ between the primary and secondary images available according to the above two equations can be expressed as:
with a main antenna A 1 And a secondary antenna A 2 The plane perpendicular to the ground is a yoz plane, a space rectangular coordinate system is established, and the space coordinates of the two radars are respectively as follows:
A 1 (0,0,H)
A 2 (0,Bcosα,H+Bsinα)
the spatial coordinates of the target P and its projection P' on the reference plane may be set as:
P(x,y,h)
P'(x,y,0)
in the above formula, x, y and h are unknown, and then the target elevation information h is solved through a geometric relationship. According to the basic imaging theory, the actual imaging positions of the targets in the main and auxiliary images are respectively P 1 And P 2 The space coordinates are respectively:
P 1 (x 1 ,y 1 ,0)
P 1 (x 1 ,y 1 ,0)
the above coordinates are available in the actual imaging result. Antenna A 2 The projected point on the xoy plane is
A' 2 (0,Bcosα,0)
OP ' and A ' are obtained ' 2 The spatial linear equation of P' is respectively:
and (3) combining the two formulas to obtain:
the spatial coordinates of P' can be expressed as:
the length of OP' can then be determined:
from the pythagorean theorem and the geometric relationship, the height h of the target is:
the above formula represents an inverse formula of the elevation information of the target in the bunching mode. Therefore, the real elevation information of the target can be inverted according to the interferometric model of the video SAR and the phase unwrapping result.
And performing the following processing on the imaging result of each video synthetic aperture radar sub-aperture:
and an airborne double-antenna mode is adopted for interferometry, and two SAR images can be obtained in each sub-aperture. The primary and secondary SAR images in the sub-aperture need to be registered first. Image registration is to acquire reliable interference phases for accurate generation of interferograms of the sub-apertures. The main and auxiliary images obtained by the video SAR not only have the deviation of the geometric position, but also have rotation or mapping transformation, and a registration algorithm capable of detecting the change of the image view angle needs to be selected.
And selecting an SIFT registration algorithm based on feature information matching for complex image matching, wherein the SIFT registration algorithm can be used for processing the matching problem under the conditions of translation, rotation and affine transformation between two images. SIFT (Scale-invariant feature transform) is an algorithm based on feature point matching, which is also called a Scale-invariant feature transform matching algorithm, and SIFT registration algorithm satisfies invariance to both rotation and Scale transform and has good robustness to noise and view angle change. The main flow of the SIFT registration algorithm is as follows:
firstly, extracting feature points. The feature points are points that do not disappear due to scale conversion or change in viewing angle, such as bright points in dark areas, dark points in bright areas, edge points, and the like. In this step, the pixel positions of all satisfied feature points in the image are mainly searched, and possible rotation and scale-invariant feature points are identified through a gaussian differential function.
And secondly, positioning the feature points and judging the feature direction. And determining the scale and the position of the feature point by using a fitting model for all the candidate feature points. One or more feature directions are then determined for each feature point based on the gradient directions of the local image. The position, direction and scale of the feature point are the main basis for transforming all non-feature point images.
And thirdly, establishing a mapping relation. And finding a plurality of pairs of mutually matched characteristic points by pairwise comparison of characteristic vectors of all the characteristic points, fitting a mapping polynomial through the matched characteristic points, and finally establishing a mapping relation. The specific processing flow of the SIFT registration algorithm is shown in fig. 2.
After the matching of the feature points is completed, fitting of a matching polynomial is performed according to the least square principle, wherein a quaternary quadratic polynomial is selected as follows:
in the above formula, x and y are respectively the azimuth coordinate and the range coordinate of a certain feature point in the main image, and Δ x and Δ y are respectively the distances required for the auxiliary image to be translated in the azimuth coordinate and the range coordinate relative to the main image. Substituting the matched feature points into the formula to obtain a 0 ，b 0 ，c 0 ，d 0 ，a 1 ，b 1 ，c 1 ，d 1 The 8 parameters also obtain the mapping relation of the pixel points between the main image and the auxiliary image, then the auxiliary image can be resampled, the matched auxiliary image result is obtained, and the matching process is completed.
And generating an interference pattern. The interferometric technique is to invert elevation information by the phase difference of the primary and secondary images. In the above steps, the generated main and auxiliary images are registered and resampled, and then the main and auxiliary images are subjected to conjugate multiplication to obtain an interferogram of the target under the sub-aperture. The phase in the interferogram represents the phase error caused by the different distances between the antenna and the same target under different viewing angles, and the video SAR interferometry is to derive the elevation information of the target according to an interferometric model and interferometric phases.
According to the interferometry model shown in the attached drawing 1, because the imaging included angle of the fixed video SAR system is fixed, when the range of an imaging scene is determined, the distance between the airborne radar platform and the center of the scene is also determined, so that the distance between the radar and the scene area is far longer than the length of the radar base line, and the horizontal base line B can be obtained || Comprises the following steps:
then perpendicular to base line B ⊥ Can be expressed as:
the interference phase is different in the slant distance of the radar main antenna and the radar auxiliary antenna to the measurement target, and the phase difference Δ Φ generated by the difference of the slant distances can be expressed as:
the elevation information h of the measurement target may be expressed as:
h＝H-R 1 cosθ
in order to conveniently use the phase difference delta phi to express the elevation information h, respectively deriving the delta phi and the h to theta to obtain:
then the relationship between the elevation information h and the phase difference Δ φ can be obtained:
the relationship between the elevation inversion accuracy and the interference fringe density of the interferogram can be obtained according to the formula.
And (5) phase unwrapping. After the phase conjugate multiplication is carried out on the main image and the auxiliary image obtained by the video SAR interferometry system, the phase value in the obtained interferogram is the main value in the interference phase, and the range is [0,2 pi ] or [ -pi, pi). At the fringe of the interference pattern, the phase value will jump in a step manner, the phase value will change back and forth between 0 and 2 pi, and the interference phase before and after the change will differ by one or more integer periods. The purpose of phase unwrapping is to obtain the complete cycle number of the phase difference between interference phases in the whole interference pattern, so as to obtain an actual phase value, and then the actual elevation information of the ground target can be inverted according to the interferometric measurement model.
And phase unwrapping the sub-aperture interferogram. In order to calculate the elevation value of the ground target through the interference phases, the whole period number of the phase difference between the interference phases in the whole interference image must be determined, namely the phase unwrapping processing is carried out on the interference image. Based on the characteristic that the measurement range of the airborne platform is small, the method adopts a least square phase unwrapping method based on an error equation, and the unwrapping result can be expressed as follows:
Φ＝(A T A) -1 A T L
and (4) performing elevation inversion. If with phi 0 Shows the interference phase offset, phi' shows the interference phase after unwrapping, and lambda shows the video synthetic aperture radar wavelength, then the slant range difference DeltaR is
The elevation value h of the corresponding ground target is
According to the formula, the height information of the target can be obtained through the phase information, and the video synthetic aperture radar interferometry is realized.
Provided is a video SAR interferometry process method. According to the key process, the difference between the video SAR interferometric measurement and the traditional InSAR is obtained, firstly, in an imaging mode, the video SAR uses beam bunching mode imaging, and the traditional InSAR uses strip imaging, so that an interferometric model needs to be reestablished, an elevation inversion formula is deduced according to the geometric relation in the interferometric model, and secondly, the problem of view angle deviation of main and auxiliary images needs to be solved, and an algorithm for registering the images with view angle transformation is needed. Then, the steps of interferogram generation, phase unwrapping, and the like in the interferometric step need to be verified. And finally, the generated DEM needs to be corrected according to the main antenna to obtain the real terrain of the target area. The results of the video SAR interferometry are shown in fig. 3.
A multi-aperture data fusion method.
The video SAR is used as a novel synthetic aperture radar with high imaging frame rate and short wavelength, can continuously irradiate an imaging area in a circumferential beam-bunching mode around the center of a scene area, can obtain multiple groups of measurement data in a short time, and can also obtain measurement data of multiple visual angles around the imaging area. Therefore, compared with the traditional strip-type InSAR, the interferometric measurement based on the video SAR can obtain the measurement results under different viewing angles, the interferometric measurement of the measurement result obtained by each sub-aperture can obtain the height information of an imaging measurement area under the viewing angle, the height inversion results of a plurality of sub-apertures are subjected to data fusion, the unreliable data which are caused by shadow or overlapping phenomena in the inversion results can be eliminated, and the precision of the height inversion is improved by using a large amount of sample data of the interferometric measurement of the video SAR.
Because the video SAR system works in the terahertz frequency band, the synthetic aperture accumulation angle of the video SAR system is small, so that the imaging results of a plurality of sub-apertures can be obtained in a short time, and the data sample can be expanded rapidly. And the video SAR system works in a circumferential bunching mode, can continuously irradiate the same target area to obtain elevation inversion results of the target area at different viewing angles, and can obtain more accurate inversion results by performing data fusion on all elevation information data.
Suppose that the video SAR system obtains n groups of sample data of a target area as D 1 ,D 2 ,D 3 ,…,D n-1 ,D n For any coordinate (x, y) in the target area, there are n sets of elevation sample data H 1 ,H 2 ,H 3 ,…,H n-1 ,H n The n sets of elevation sample data need to be screened, and the unreliable data are removed, so that the measurement accuracy is improved. It is assumed that the N sets of sample data obey a normal distribution, i.e., H to N (μ, σ) 2 ) Given a confidence level of 0.9 and a significance level of α ═ 0.1, it is necessary to first find a mean value e (h) of the elevation sample data as:
in the above formula, the first and second carbon atoms are,
represents the mean of the sample data, using S 2 Represents the variance d (h) of the elevation sample data, namely:
on the premise that the elevation sample data obeys normal distribution, a confidence interval with a confidence of 0.9 about H can be obtained as follows:
after the confidence interval is obtained, the elevation sample data is required to be screened according to the confidence interval, the sample data in the confidence interval is reserved, otherwise, the sample data is discarded, and therefore the data with larger difference with the average elevation value can be screened out. Assuming that m groups of elevation sample data obtained after screening are h 1 ,h 2 ,h 3 ,…,h m-1 ,h m Calculating the mean value of the m groups of data
Averaging the obtained data
And the elevation values are used as the elevation values of the scene coordinates (x, y), then the elevation values of the rest coordinates in the scene are calculated, and finally the three-dimensional information corresponding to all the coordinates in the imaging scene is obtained. From the point of view of mathematical statistics, the confidence interval can roughly screen sample data, eliminate non-credible data and then credible dataAnd averaging, so that credible data can be retained to a great extent, and the elevation information of the coordinate point is obtained. In addition, in the actual measurement process, the obtained data inevitably have deviation, and the influence of error data can be reduced to the maximum extent by using the processing method introduced in this section, so that the accuracy of the finally obtained elevation inversion data is improved. The specific processing flow of the multi-sample data fusion of the video SAR interferometry system is shown in FIG. 4.
The specific flow of the method of the present invention is shown in fig. 1, fig. 2, fig. 3 and fig. 4. The center frequency of a video synthetic aperture radar system is set to be 220GHz, the bandwidth is set to be 2GHz, the height of the radar is set to be 1200m, the ground is used as a reference plane, the main antenna and the auxiliary antenna are vertically arranged, the length of a base line is 5m, and the airborne radar platform performs approximate linear motion on a preset track. The target is set as a hill model. An interferometric model as shown in fig. 1 is established according to system parameters, and an elevation inversion formula of a target can be obtained according to targets at different positions. And then imaging the received sub-aperture data to obtain a main image and an auxiliary image in each sub-aperture, registering according to the steps shown in fig. 2, performing conjugate multiplication on each group of main and auxiliary images to obtain an interference image, performing phase unwrapping on the interference image, and performing elevation inversion on the target to obtain elevation information of the target in each sub-aperture. Finally, a video SAR interferometry flow shown in fig. 3 is established according to the flow, and the method shown in fig. 4 is used to improve the interferometry precision by utilizing the advantage of high frame rate of the video SAR.
Claims (2)
1. An interferometry method based on a video synthetic aperture radar is used for an airborne double-antenna interferometric synthetic aperture radar system and is characterized by comprising the following steps:
s1, establishing a coordinate system according to the imaging model of the video synthetic aperture radar by using the vertical plane where the main antenna and the auxiliary antenna are located, and establishing an inversion formula of the elevation information of the target in the video synthetic aperture radar bunching mode:
where H is the height of the main antenna, O is the origin of the coordinate system, P' is the projection of the target P on the ground, R 1 Is the slant distance of the main antenna, alpha is the included angle between the connecting line between the main antenna and the auxiliary antenna and the horizontal plane, B is the distance between the main antenna and the auxiliary antenna, and the actual imaging positions of the target in the main and auxiliary images are respectively P 1 And P 2 ，P 1 (x 1 ,y 1 ,0)，P 2 (x 2 ,y 2 ,0)；
S2, carrying out interference measurement by adopting an airborne double-antenna mode, obtaining two synthetic aperture radar images in each sub-aperture, and registering the main synthetic aperture radar image and the auxiliary synthetic aperture radar image in the sub-aperture by utilizing an SIFT algorithm;
s3, performing conjugate multiplication on the main and auxiliary complex images generated after registration to obtain an interferogram of the target under the sub-aperture, wherein the phase in the interferogram represents the phase error caused by different distances between the antenna and the same target under different angles of view, and the relation between elevation information h and a phase difference delta phi is obtained:
wherein theta is an included angle between the main antenna and the target, and lambda represents the wavelength of the video synthetic aperture radar;
s4, performing phase unwrapping on the obtained interferogram by using a least square phase unwrapping method based on an error equation to obtain an unwrapped interference phase;
s5, elevation inversion: is measured by phi 0 Indicates the interference phase offset, phi' indicates the interference phase after unwrapping, and the skew difference DeltaR is
The elevation value h of the corresponding ground target is as follows:
the height information of the target can be obtained through the phase information, and the video synthetic aperture radar interferometry is realized.
2. The interferometry method based on video synthetic aperture radar according to claim 1, further comprising:
s6, multi-aperture data fusion: suppose that the video synthetic aperture radar system obtains n groups of sample data of a target area as D 1 ,D 2 ,D 3 ,…,D n-1 ,D n For any coordinate (x, y) in the target area, there are n sets of elevation sample data H 1 ,H 2 ,H 3 ,…,H n-1 ,H n Screening the n groups of elevation sample data, and eliminating unreliable data to improve the measurement accuracy; the N sets of elevation sample data are assumed to follow a normal distribution, i.e., H-N (μ, σ) 2 ) Given a confidence level of 0.9 and a significance level of β ═ 0.1, it is necessary to first determine a mean value e (h) of the elevation sample data as:
in the above formula, the first and second carbon atoms are,
represents the mean of the sample data, using S 2 Represents the variance d (h) of the elevation sample data, namely:
on the premise of assuming that the elevation sample data obeys normal distribution, a confidence interval with a confidence of 0.9 about H is obtained as follows:
after the confidence interval is obtained, the elevation sample data are screened according to the confidence interval, the sample data in the confidence interval are reserved, otherwise, the sample data are abandoned, and the m groups of elevation sample data obtained after screening are assumed to be h 1 ,h 2 ,h 3 ,…,h m-1 ,h m Calculating the mean value of the m groups of data
Averaging the obtained data
And the elevation values are used as the elevation values of the scene coordinates (x, y), then the elevation values of the rest coordinates in the scene are calculated, and finally the three-dimensional information corresponding to all the coordinates in the imaging scene is obtained.
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