CN111896954A - Corner reflector coordinate positioning method for shipborne SAR image - Google Patents
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Abstract
The invention discloses a corner reflector coordinate positioning method of a shipborne SAR image, which comprises the following steps: selecting a corner reflector, calculating SAR image characteristics, calculating spatial characteristics, correcting characteristic points and deducing a central point of the corner reflector; based on the scale space, the invention considers the radiation characteristic and the space characteristic of the corner reflector in the SAR image, and after verification, the invention has equivalent precision and identical result for the average relative error and the root mean square error of the corner reflector positioning result of the high-resolution shipborne SAR image and the corner reflector coordinate positioning result after geometric correction based on the control point in the distance direction and the azimuth direction, thereby proving that the invention does not depend on the geographic coordinate information of the corner reflector, the corner reflector coordinate positioning precision can reach the sub-pixel level, and the azimuth coordinate positioning precision is superior to the distance direction coordinate because the focusing effect of the corner reflector in the azimuth direction is superior to the distance direction coordinate.
Description
Technical Field
The invention relates to the technical field of coordinate positioning, in particular to a corner reflector coordinate positioning method of a shipborne SAR image.
Background
The corner reflector can strongly reflect radar beams due to the particularity of the design of the corner reflector, particularly, echoes of the corner reflector are overlapped for many times in the imaging process of the synthetic aperture radar, a high-brightness area is presented in an SAR image, and then the scattering characteristic can be widely applied to external calibration of a radar system, indirect representation of ground micro-deformation, image registration basis, image restoration, CRINSAR technology and the like;
corner reflector positioning, which refers to a process of obtaining accurate SAR image coordinates corresponding to a centroid of a corner reflector, is fundamental work of corner reflector related application, and about the research of the corner reflector on the coordinate positioning in an SAR image, the method mainly focuses on satellite-borne SAR images, because the resolution of the satellite-borne SAR images is low, the images of the corner reflectors generally show highlight points or areas and have no obvious cross-hair characteristics, the commonly used methods for corner reflector positioning are mostly based on the radiation intensity characteristics of the corner reflectors, such as a template matching method based on intensity characteristics, a peak zero filling method, a method of a spectral correlation diagram and the like, other types of methods also comprise a method based on change detection, a dual threshold method based on PSInSAR, a comprehensive index multiple method based on intensity and coherence coefficients, a detection method based on prior knowledge and the like, and most of the methods can only achieve positioning accuracy at a level, such as template matching, spectral correlation, etc.; a small part of methods which can reach the accuracy of sub-pixel levels, such as a peak zero filling method, are influenced by factors such as background and noise, the positioning effect is difficult to achieve expectation, the characteristics of a cross wire formed by imaging a corner reflector in a high-resolution shipborne SAR image are obvious, the image coordinate positioning accuracy of the corner reflector has the potential of further improvement, and the method has important significance for obtaining the image coordinates of the sub-pixel levels with high accuracy by taking the corner reflector as a ground control point in the subsequent operation of using the shipborne SAR for interferometry and DEM extraction;
the identification of the corner reflector can be combined with the characteristics of gray scale, shape and the like expressed in the SAR image, and for a high-resolution shipborne SAR image, the characteristics of the corner reflector are rich, so that the identification strategies and the coordinate positioning method are more, according to the existing research, in the coordinate positioning method of the common corner reflector in the SAR image, for example, the method based on the radiation intensity characteristic is easily influenced by noise, the method based on the characteristic parameter can not reach the ideal precision, and the method based on the radiation calibration and the geometric correction needs to carry out field measurement on the corner reflector to obtain the geographic coordinate, which wastes time and labor, so the invention provides the corner reflector coordinate positioning method of the shipborne SAR image to solve the problems in the prior art.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a corner reflector coordinate positioning method for a shipborne SAR image, which does not depend on geographic coordinate information of a corner reflector, and the corner reflector coordinate positioning accuracy can reach a sub-pixel level.
In order to realize the purpose of the invention, the invention is realized by the following technical scheme: a corner reflector coordinate positioning method of a shipborne SAR image comprises the following steps:
the method comprises the following steps: selective angle reflector
The method is characterized in that the whole RCS curve corresponding to the triangular conical corner reflector changes slowly, the RCS value reduction speed is slowest within the range of deviating from the maximum incidence direction by 40 degrees, and the triangular conical corner reflector has large tolerance to radar incident wave deviation, so that the triangular conical corner reflector is used as a common corner reflector, SAR is used for recording the amplitude and phase information of backscattered electromagnetic waves of the triangular conical corner reflector in an image form, an intensity map of the triangular conical corner reflector is obtained after the amplitude value is calibrated and squared, and the RCS of the triangular conical corner reflector is obtained on the intensity map, wherein the unit is m2；
Step two: SAR image feature computation
Regarding the backscattering signal of the triangular conical corner reflector to the SAR as an impulse response function, in a focused SAR image, the envelope surface of the expressed signal is as follows:
wherein h (x, t) represents the impulse response function of the t-x plane, LSFor synthesis of the pore time, τρIs the pulse width, t is the ramp time, x is the azimuth angle, ρrFor distance resolution, paFor azimuth resolution, the triangular conical corner reflector is obtained by the formula (1), and in an ideal state, the intensity is expressed in a sinc function form in the azimuth direction and the distance direction, so that the triangular conical corner reflector is expressed in a cross-hair shape in a high-resolution SAR image;
step three: spatial feature computation
Expressing the Gaussian and Gaussian difference scale space obtained by the triangular conical corner reflector imaging area as follows:
in the formula, E (t, x) represents E (h (t, x)), G (t, x, σ) represents a gaussian convolution kernel whose spatial scale is σ, L (t, x, σ), D (t, x, σ) represent a gaussian scale space and a gaussian difference scale space, respectively, and k is a ratio between spatial scales of two layers of gaussian scale spaces, as can be seen from formula (2), D (t, x, σ), spatial scale σ, and image resolution ρa，ρrCorrelation;
step four: feature point correction
Establishing a Gaussian pyramid and a Gaussian difference pyramid by the formula (2), detecting extreme points, obtaining a characteristic point X in a scale space, and correcting the X:
where X ═ t, X, σ, X is the imaging target point,
is the result after X correction;
step five: derivative corner reflector center point
In actual processing, the number of feature points detected in the triangular pyramidal retroreflector imaging region is large, and the centroid of the retroreflector is detected as a feature point at a certain scale σ based on imaging feature formula (1) of the retroreflector, and therefore the centroid of the retroreflector corresponds to the imaging point in the feature point set P ═ X1,X2,...,XnAnd (4) screening, wherein according to the existing corner reflector coordinate positioning method: the template matching method and the peak zero-filling method firstly acquire an approximate coordinate X' of the corner reflector, and when the formula (4) is satisfied, the characteristic point is considered as the center point of the corner reflector:
|Xi-X′|＜R (4)
wherein R is a distance threshold, i is 1,2, …, n.
The further improvement lies in that: in the first step, RCS is a radar scattering cross section and represents the echo intensity and the backscattering energy of the target generated after the radar transmits the electromagnetic waves, and RCS is a function consisting of frequency, incident wave polarization, receiving antenna polarization, target shape, structure and material characteristic factors and has no direct relation with the area of the target displayed on radar beams.
The further improvement lies in that: in the second step, in the focused SAR image, the echo energy distribution of the triangular conical corner reflector is similar to the point spread function PSF of the optical system.
The further improvement lies in that: in the third step, the imaging of the triangular conical corner reflector not only has obvious radiation characteristics, but also has spatial characteristics, and under the condition of different image resolutions, the imaging blur degree of the triangular conical corner reflector is different and is similar to the scale space of the image.
The further improvement lies in that: in the fourth step of the method, the first step of the method,
and the corrected result of X comprises the precise coordinates of the characteristic points and the scale parameters.
The further improvement lies in that: in the fifth step, the size of the sigma is related to the size of the triangular conical corner reflector and the resolution of the shipborne SAR image.
The invention has the beneficial effects that: based on a scale space, the radiation characteristic and the space characteristic of a corner reflector in an SAR image are considered at the same time, and verification proves that the positioning accuracy of the corner reflector of a high-resolution shipborne SAR image is equivalent to the accuracy of the average relative error and the root mean square error of the coordinate positioning result of the corner reflector after geometric correction based on a control point in the distance direction and the azimuth direction, the results are identical, and the result proves that the positioning accuracy of the corner reflector can reach the sub-pixel level without depending on the geographic coordinate information of the corner reflector, and the focusing effect of the corner reflector in the azimuth direction is superior to that of the distance direction, so the positioning accuracy of the azimuth coordinate is superior to that of the distance direction coordinate, and compared with the distance direction, the strong reflection pixel in the azimuth direction is more, the details are more abundant, and the positioning accuracy is closer to the ideal imaging situation of the corner reflector.
Drawings
FIG. 1 is a RCS graph of a triangular pyramidal corner reflector of the present invention;
FIG. 2 is a three-dimensional perspective of the sinc function of the present invention;
FIG. 3 is a diagram of the triangular pyramidal corner reflector imaging of the present invention;
FIG. 4 is an imaging feature map of the corner reflector at a resolution of 241 × 241 images of 0.25m in accordance with the present invention;
FIG. 5 is an imaging feature map of the corner reflector at 1m, 61X 61 image resolution according to the present invention;
FIG. 6 is an imaging feature map of the corner reflector at 2m, 31X 31 image resolution according to the present invention;
FIG. 7 is an image feature map of the corner reflector at 4m, 16X 16 image resolution in accordance with the present invention;
FIG. 8 is a graph of corner reflector coordinate positioning error of the present invention;
FIG. 9 is a spatial scale view of a corner reflector centering feature of the present invention;
FIG. 10 is a graph of the coordinate difference between the present invention and the verification data.
Detailed Description
In order to further understand the present invention, the following detailed description will be made with reference to the following examples, which are only used for explaining the present invention and are not to be construed as limiting the scope of the present invention.
As shown in fig. 1,2 and 3, the present embodiment provides a method for positioning coordinates of a corner reflector of a ship-borne SAR image, including the following steps:
the method comprises the following steps: selective angle reflector
As the whole RCS curve corresponding to the triangular conical corner reflector changes slowly and the RCS value reduction speed is slowest within the range of deviating from the maximum incidence direction by 40 degrees, as shown in figure 1, the triangular conical corner reflector has large tolerance to the radar incident wave deviation, so the triangular conical corner reflector is taken as a commonly used corner reflector, the RCS is a radar scattering sectional area and represents the echo intensity and the backscattering energy of a target generated after the radar transmits an electromagnetic wave, and the RCS is a function consisting of frequency, incident wave polarization, receiving antenna polarization, target shape, structure and material characteristic factors and is a function consisting of frequency, incident wave polarization, receiving antenna polarization, target shape, structure and material characteristic factorsThere is no direct relationship to the area that the target exhibits on the radar beam; then, utilizing SAR to record the amplitude and phase information of the backscattering electromagnetic wave of the triangular conical corner reflector in the form of image, calibrating and squaring the amplitude value to obtain the intensity map of the triangular conical corner reflector, and obtaining the RCS of the triangular conical corner reflector on the intensity map, wherein the unit is m2；
Step two: SAR image feature computation
Regarding a backscattering signal of the triangular conical corner reflector to the SAR as an impulse response function, in a focused SAR image, the echo energy distribution of the triangular conical corner reflector is similar to a point spread function PSF of an optical system, and the envelope surface of the expressed signal is as follows:
wherein h (x, t) represents the impulse response function of the t-x plane, LSFor synthesis of the pore time, τρIs the pulse width, t is the ramp time, x is the azimuth angle, ρrFor distance resolution, paFor the azimuth resolution, the triangular conical corner reflector is obtained by the formula (1), and in an ideal state, the intensity is expressed in a sinc function form in the azimuth direction and the distance direction, as shown in fig. 2, so that the triangular conical corner reflector is expressed in a cross-hair shape in a high-resolution SAR image; as shown in FIG. 3;
step three: spatial feature computation
The imaging of the triangular conical corner reflector not only has obvious radiation characteristics, but also has spatial characteristics, under the condition of different image resolutions, the imaging blur degree of the triangular conical corner reflector is different and is similar to the scale space of an image, and the Gaussian difference scale space obtained by the imaging area of the triangular conical corner reflector is expressed as follows:
in the formula, E (t, x) represents E (h (t, x)), G (t, x, σ) represents a Gaussian convolution kernel having a spatial scale σ, and L (t, x, σ),D (t, x, sigma) represents a Gaussian scale space and a Gaussian difference scale space respectively, k is the ratio of the spatial scales of two layers of Gaussian scale spaces, and D (t, x, sigma) and the spatial scale sigma as well as the image resolution rho can be known from the formula (2)a，ρrCorrelation;
step four: feature point correction
Establishing a Gaussian pyramid and a Gaussian difference pyramid by the formula (2), detecting extreme points, obtaining a characteristic point X in a scale space, and correcting the X:
where X ═ t, X, σ, X is the imaging target point,
the result after X correction comprises the precise coordinates and the scale parameters of the characteristic points;
step five: derivative corner reflector center point
In actual processing, the number of feature points detected in the triangular conical corner reflector imaging area is large, according to the imaging feature formula (1) of the corner reflector, the centroid of the corner reflector is detected as a feature point in a certain scale sigma, and the size of sigma is related to the size of the triangular conical corner reflector and the resolution of the ship-borne SAR image, so that the centroid of the corner reflector corresponds to the imaging point in a feature point set P { X ═ X { (X) }1,X2,...,XnAnd (4) screening, wherein according to the existing corner reflector coordinate positioning method: the template matching method and the peak zero-filling method firstly acquire an approximate coordinate X' of the corner reflector, and when the formula (4) is satisfied, the characteristic point is considered as the center point of the corner reflector:
|Xi-X′|＜R (4)
wherein R is a distance threshold, i is 1,2, …, n.
Simulation test:
in order to verify the feasibility of corner reflector coordinate positioning based on a scale space, corner reflector imaging with different resolutions is simulated, and coordinate positioning is performed on a corner reflector central point based on the scale space.
Assuming that the resolutions of the azimuth direction and the range direction of the SAR image are the same, at the moment, only the positioning accuracy of the range direction coordinate needs to be considered, the simulation parameters comprise range direction bandwidth, range direction sampling frequency, range direction resolution and the like, the range direction bandwidth is 600MHz, under the condition of different range direction resolutions, the imaging simulation result of the corner reflector is shown in figures 4-7, the higher the image resolution is, the larger the number of pixels occupied by the bright area of the corner reflector is, and the more the details are.
And establishing a Gaussian and Gaussian difference pyramid for the corner reflector region images with different resolutions by using a siftDemo V4 program, detecting the characteristic points, screening out the characteristic points close to the central point of the image, and comparing the characteristic points with the coordinates of the central point (the central point of the image) of the real corner reflector. Under the condition of different distance-direction resolutions, the coordinate positioning error of the central point of the corner reflector and the corresponding spatial scale are respectively shown in fig. 8 and fig. 9. In fig. 8, under the condition of different resolutions (0 to 6m), the positioning accuracy of the central point of the corner reflector is extremely high (within 0.02 pixel error), and in fig. 9, the image resolution and the spatial scale of the feature point corresponding to the center of the corner reflector exhibit a strong inverse proportion relationship, which indicates that the imaging area of the corner reflector has a strong spatial scale characteristic, and the higher the image resolution is, the larger the spatial scale of the imaging area of the corner reflector is. Fig. 8 and 9 demonstrate the feasibility of corner reflector coordinate positioning based on scale space.
And (3) testing:
further verification is carried out by adopting ship-borne SAR measured data, the main parameters of the ship-borne SAR image are shown in a table 1, and a double-antenna rail-crossing imaging mode is adopted. The corner reflector has good imaging condition in the shipborne SAR image, and is in a more obvious cross-hair shape.
TABLE 1 Main parameters of shipborne SAR images
The control net is arranged at the central position of the corner reflector, and the accurate geographic coordinates of the central position of the corner reflector are obtained by using the traditional measuring means (total station forward intersection measurement), wherein errors in the measurement of the point coordinates are less than 6 mm.
And interpolating the imaging area of the corner reflector to 0.01 pixel by adopting a peak zero filling method to obtain image coordinates of the center points of all corner reflectors, selecting the corner reflectors CR7 and CR9 as geometric correction control points, and performing geometric correction by combining a Doppler imaging model and an affine transformation optimization model to obtain a high-precision image coordinate result of the corner reflector as shown in table 2. The results of table 2 can be made as comparative data for the corner reflector coordinate positioning method herein.
TABLE 2 geometric correction of relief reflector image coordinates
The specific coordinate positioning result of the corner reflector based on the scale space is shown in table 3, and by analyzing table 3, we know that the feature point scale values corresponding to all corner reflectors are close, and the sizes of all the triangular pyramid type corner reflectors arranged are the same, which is consistent with the simulation result of fig. 9, that is, for the corner reflectors with the same size, the feature points are detected on the same scale.
TABLE 3 corner Reflector coordinate positioning results based on scale space
The difference between the coordinate positioning result of the corner reflector based on the spatial scale and the comparison data obtained by combining the tables 2 and 3 is shown in fig. 10, and the average relative error and the root mean square error result of the coordinate positioning result and the comparison data obtained by the method are shown in table 4.
Table 4 error of the method and comparative data herein
Analyzing the above results in conclusion:
(1) the method has the advantages that the average relative error and the root mean square error of the corner reflector positioning result of the high-resolution shipborne SAR image and the corner reflector coordinate positioning result after geometric correction based on the control point in the distance direction and the azimuth direction are less than 0.31 pixel, and the accuracy is equivalent, which shows that the positioning of the corner reflector in the shipborne SAR image in the method can reach sub-pixel level accuracy under the condition of no ground control point;
(2) the results in table 3 indicate that the positioning accuracy of the azimuth coordinate is better than that of the distance coordinate because the focusing effect of the corner reflector in the azimuth direction is better than that of the distance direction, and compared with the distance direction, the strong reflection pixels in the azimuth direction are more, the details are richer and are closer to the ideal imaging situation of the corner reflector.
The corner reflector coordinate positioning method of the shipborne SAR image is based on a scale space, simultaneously considers the radiation characteristic and the space characteristic of a corner reflector in the SAR image, and after verification, the invention proves that the average relative error and the root mean square error of the corner reflector positioning result of the high-resolution shipborne SAR image and the corner reflector coordinate positioning result after geometric correction based on a control point in the distance direction and the azimuth direction are less than 0.31 pixel, the precision is equivalent, the result is identical, the result proves that the method does not depend on the geographic coordinate information of the corner reflector, the corner reflector coordinate positioning precision can reach the sub-pixel level, and the focusing effect of the corner reflector in the azimuth direction is superior to that in the distance direction, therefore, the positioning accuracy of the azimuth coordinate is superior to that of the distance coordinate, and compared with the distance coordinate, the azimuth upward strong reflection image elements are more, the details are richer, and the azimuth upward strong reflection image elements are closer to the ideal imaging situation of the corner reflector.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. A corner reflector coordinate positioning method of a shipborne SAR image is characterized by comprising the following steps:
the method comprises the following steps: selective angle reflector
The method is characterized in that the whole RCS curve corresponding to the triangular conical corner reflector changes slowly, the RCS value reduction speed is slowest within the range of deviating from the maximum incidence direction by 40 degrees, and the triangular conical corner reflector has large tolerance to radar incident wave deviation, so that the triangular conical corner reflector is used as a common corner reflector, SAR is used for recording the amplitude and phase information of backscattered electromagnetic waves of the triangular conical corner reflector in an image form, an intensity map of the triangular conical corner reflector is obtained after the amplitude value is calibrated and squared, and the RCS of the triangular conical corner reflector is obtained on the intensity map, wherein the unit is m2；
Step two: SAR image feature computation
Regarding the backscattering signal of the triangular conical corner reflector to the SAR as an impulse response function, in a focused SAR image, the envelope surface of the expressed signal is as follows:
wherein h (x, t) represents the impulse response function of the t-x plane, LSFor synthesis of the pore time, τρIs the pulse width, t is the ramp time, x is the azimuth angle, ρrFor distance resolution, paFor azimuth resolution, the triangular conical corner reflector is obtained by the formula (1), and in an ideal state, the intensity is expressed in a sinc function form in the azimuth direction and the distance direction, so that the triangular conical corner reflector is expressed in a cross-hair shape in a high-resolution SAR image;
step three: spatial feature computation
Expressing the Gaussian and Gaussian difference scale space obtained by the triangular conical corner reflector imaging area as follows:
in the formula, E (t, x) represents E (h (t, x)), G (t, x, σ) represents a gaussian convolution kernel whose spatial scale is σ, L (t, x, σ), D (t, x, σ) represent a gaussian scale space and a gaussian difference scale space, respectively, and k is a ratio between spatial scales of two layers of gaussian scale spaces, as can be seen from formula (2), D (t, x, σ), spatial scale σ, and image resolution ρa，ρrCorrelation;
step four: feature point correction
Establishing a Gaussian pyramid and a Gaussian difference pyramid by the formula (2), detecting extreme points, obtaining a characteristic point X in a scale space, and correcting the X:
where X ═ t, X, σ, X is the imaging target point,
is the result after X correction;
step five: derivative corner reflector center point
In actual processing, the number of feature points detected in the triangular pyramidal retroreflector imaging region is large, and the centroid of the retroreflector is detected as a feature point at a certain scale σ based on imaging feature formula (1) of the retroreflector, and therefore the centroid of the retroreflector corresponds to the imaging point in the feature point set P ═ X1,X2,...,XnAnd (4) screening, wherein according to the existing corner reflector coordinate positioning method: the template matching method and the peak zero-filling method firstly acquire an approximate coordinate X' of the corner reflector, and when the formula (4) is satisfied, the characteristic point is considered as the center point of the corner reflector:
|Xi-X′|＜R (4)
wherein R is a distance threshold, i is 1,2, …, n.
2. The corner reflector coordinate positioning method for the shipborne SAR image according to claim 1, characterized in that: in the first step, RCS is a radar scattering cross section and represents the echo intensity and the backscattering energy of the target generated after the radar transmits the electromagnetic waves, and RCS is a function consisting of frequency, incident wave polarization, receiving antenna polarization, target shape, structure and material characteristic factors and has no direct relation with the area of the target displayed on radar beams.
3. The corner reflector coordinate positioning method for the shipborne SAR image according to claim 1, characterized in that: in the second step, in the focused SAR image, the echo energy distribution of the triangular conical corner reflector is similar to the point spread function PSF of the optical system.
4. The corner reflector coordinate positioning method for the shipborne SAR image according to claim 1, characterized in that: in the third step, the imaging of the triangular conical corner reflector not only has obvious radiation characteristics, but also has spatial characteristics, and under the condition of different image resolutions, the imaging blur degree of the triangular conical corner reflector is different and is similar to the scale space of the image.
5. The corner reflector coordinate positioning method for the shipborne SAR image according to claim 1, characterized in that: in the fourth step of the method, the first step of the method,
and the corrected result of X comprises the precise coordinates of the characteristic points and the scale parameters.
6. The corner reflector coordinate positioning method for the shipborne SAR image according to claim 1, characterized in that: in the fifth step, the size of the sigma is related to the size of the triangular conical corner reflector and the resolution of the shipborne SAR image.
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