CN114325700A - Satellite-borne multi-channel SAR moving target imaging method - Google Patents
Satellite-borne multi-channel SAR moving target imaging method Download PDFInfo
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Abstract
The invention relates to a satellite-borne multi-channel SAR moving target imaging method, which belongs to the field of synthetic aperture radars and comprises the following steps: step S1: estimating the inter-channel amplitude-phase error based on the internal calibration data, and performing coarse imaging on sea clutter and moving targets by adopting a frequency spectrum reconstruction algorithm and a linear frequency modulation and scaling algorithm; step S2: detecting a moving target and a false target in the coarse imaging by adopting a constant false alarm detection method; step S3: establishing a quantitative relation among an inter-channel phase error, a false target amplitude and a moving target moving speed caused by moving of a moving target; step S4: carrying out inverse imaging to obtain a precise imaging result of each moving target; step S5: and superposing the fine imaging results of all the moving targets and the rough imaging results of the sea clutter to obtain a final imaging result without false targets. The invention realizes effective suppression of false targets and improves the imaging quality.
Description
Technical Field
The invention relates to the technical field of synthetic aperture radars, in particular to a satellite-borne multi-channel SAR moving target imaging method.
Background
Synthetic Aperture Radar (SAR) is a new system Radar with two-dimensional high-resolution imaging capability, can perform all-time and all-weather observation on an interested area, and is widely applied to the fields of geological exploration, vegetation census, ocean research, mapping, deformation detection and the like. With the continuous development of the satellite-borne SAR technology, the acquisition of high-resolution wide-width satellite-borne SAR images becomes a necessary development trend.
The multi-channel SAR system adopts a bias phase center azimuth multi-beam technology, one azimuth antenna transmits and receives multiple azimuth beams, a single sub-antenna transmits azimuth wide beams at a lower pulse repetition frequency, and a plurality of sub-antennas receive signals at different azimuths, so that echo signals of a plurality of space sampling positions are obtained, the space sampling of the signals is improved, the space sampling is replaced by time sampling, and high-resolution wide-amplitude imaging is realized. However, for multi-channel moving target imaging, target motion will cause phase errors among channels, resulting in a large number of false targets appearing in the imaging result, and seriously affecting the image quality.
Therefore, a satellite-borne multi-channel SAR moving target imaging method is needed.
Disclosure of Invention
The invention aims to provide a satellite-borne multi-channel SAR moving target imaging method, which is used for accurately estimating inter-channel phase errors introduced by target motion and realizing effective suppression of false targets.
In order to solve the technical problem, the invention provides a satellite-borne multi-channel SAR moving target imaging method, which comprises the following steps:
step S1: estimating inter-channel amplitude and phase errors based on the internal calibration data, compensating the inter-channel amplitude and phase errors introduced by hardware differences, and performing coarse imaging on sea clutter and moving targets by adopting a frequency spectrum reconstruction algorithm and a linear frequency modulation and scaling algorithm;
step S2: detecting moving targets and false targets in the coarse imaging by adopting a constant false alarm detection method, and grouping the detected moving targets and the false targets according to the position relation between the real target of the moving target and the false targets;
step S3: establishing a quantitative relation among inter-channel phase errors caused by moving target motion, false target amplitudes and moving target motion speeds, respectively estimating the inter-channel phase errors of each moving target, and respectively obtaining estimated values of the inter-channel phase errors of each moving target according to the measured false target amplitudes;
step S4: performing inverse imaging, inversely transforming the coarse imaging image domain of each group of moving targets and the corresponding false targets to an echo domain based on the inverse process of a linear frequency modulation and scaling algorithm and a spectral reconstruction algorithm, respectively compensating the phase error between channels of each moving target, and obtaining a fine imaging result of each moving target by adopting the spectral reconstruction algorithm and the linear frequency modulation and scaling algorithm;
step S5: and superposing the fine imaging results of all the moving targets and the rough imaging results of the sea clutter to obtain a final imaging result without false targets.
Optionally, if the fine imaging result obtained in step S4 still has residual false targets, step S41 is further included after step S4 and before step S5:
step S41: and (4) according to the amplitude of the residual false target, iteratively performing the steps S3 and S4 until the false target in the fine imaging result is invisible.
Optionally, in step S2, each group includes a real target of the moving target and a corresponding dummy target.
Optionally, in step S2, the grouping is performed as follows:
step S21: dividing all detected targets at the same range gate into a large group;
step S22: determining the unmarked target with the strongest energy in the large group as a real target of a certain moving target;
step S23: determining false targets, wherein Nc-1 false targets are respectively determined at two ends of a real target along the azimuth direction, and the azimuth time interval between the adjacent real target and the false target is as follows, wherein the azimuth time interval is the number of channels, the pulse repetition frequency of a single-channel signal and the Doppler frequency modulation frequency; obtaining a false target corresponding to the real target;
step S24: grouping the certain moving target and the obtained corresponding false target into a group; marking a moving target and a corresponding false target;
step S25: iterating the above steps S22-S24 until all moving objects in the large group are traversed;
step S26: the next range gate is selected and the above steps S21 to S25 are iterated, completing the grouping in step S2.
Optionally, all the detected targets include different moving targets and false targets thereof.
Optionally, after step S2, step S3 is preceded by the following steps:
and extracting the coarse imaging result of each moving target and the corresponding false target.
The satellite-borne multi-channel SAR moving target imaging method quantitatively constructs the relationship between the phase error introduced by target motion and the amplitude of a false target, accurately estimates the inter-channel phase error introduced by the target motion, realizes effective suppression of the false target and improves the imaging quality; the invention solves the problem of imaging result azimuth ambiguity caused by inter-channel phase error introduced by target motion, and makes up the defects of the prior art.
Drawings
FIG. 1 is a schematic flow chart of a satellite-borne multi-channel SAR moving target imaging method provided by the invention;
FIG. 2 is a graphical illustration of spurious target amplitude versus target radial velocity;
FIG. 3 is a schematic diagram of a simulation coarse imaging result of the satellite-borne multi-channel SAR moving target imaging method provided by the invention;
FIG. 4 is a schematic diagram of a final imaging result of satellite-borne multi-channel SAR moving target imaging provided by the invention.
Detailed Description
The satellite-borne multi-channel SAR moving target imaging method provided by the invention is further described in detail with reference to the accompanying drawings and specific embodiments. Advantages and features of the present invention will become apparent from the following description and from the claims. It is to be noted that the drawings are in a very simplified form and are not to precise scale, which is merely for the purpose of facilitating and distinctly claiming the embodiments of the present invention.
The invention provides a satellite-borne multi-channel SAR moving target imaging method, the flow of which is shown in figure 1, and the method comprises the following steps:
step S1: estimating inter-channel amplitude and phase errors based on internal calibration data, compensating the inter-channel amplitude and phase errors introduced by hardware differences, and performing coarse imaging on sea clutter and moving targets by adopting a frequency spectrum reconstruction algorithm and a linear frequency modulation Scaling (CS) algorithm;
step S2: detecting moving targets and False targets in coarse imaging by using a Constant False-Alarm Rate (CFAR) detection method, and grouping the detected moving targets and the False targets according to the position relationship between the real targets and the False targets of the moving targets, wherein each group comprises the real target of one moving target and the corresponding False target;
specifically, the real target and the false target of the moving target are located in the same range gate, and all detected targets located in the same range gate are firstly divided into a large group, where all detected targets may include different moving targets and false targets thereof, and as the amplitude of the real target of the moving target is strongest, the unmarked target with the strongest energy in the large group is the real target of a certain moving target; meanwhile, the phase error between channels introduced by the motion of the moving target will cause the real target of the moving target to respectively generate N along the two ends of the azimuth directionc1 false target, the azimuth time interval between the adjacent real target and false target being
Wherein N iscPRF is the pulse repetition frequency of the single-channel signal, fdrAdjusting the frequency for Doppler to obtain a false target corresponding to the real target; dividing the moving target and the obtained corresponding false target intoOne group; marking a moving target and a corresponding false target; the process is circulated until all the moving targets in the large group are traversed; then, another distance gate different from the distance gate is selected, the process is continued to be circulated, all moving targets and the corresponding false targets are grouped in sequence, and then the rough imaging results of all the moving targets and the corresponding false targets are extracted according to the groups.
Step S3: establishing a quantitative relation among inter-channel phase errors caused by moving targets, false target amplitudes and target moving speeds, respectively estimating the inter-channel phase errors of each moving target, and respectively obtaining estimated values of the inter-channel phase errors of each moving target according to the measured false target amplitudes;
taking the 1 st channel as a reference channel, and the phase error of the ith channel caused by the motion of the moving target is as follows:
wherein λ is the wavelength of electromagnetic wave, vrFor moving target radial velocity, d is the spacing of adjacent receive channel phase centers, vsIs the satellite velocity;
the phase error causes the real target of the moving target to respectively generate N along the two ends of the azimuth directionc1 dummy target, the amplitude | A of the left and right dummy targets closest to the real targetleftI and | ArightThe relationship between | and the moving target moving speed is as follows:
wherein, | ArealI is the true target amplitude of the moving target, C and zkiIs constant:
where i and k are integers, j is an imaginary unit, p1～pn-1Is an integer, m is an integer, whereby the left and right two false target amplitudes | A, which are closest to the true target of the moving targetleftI and | ArightA relation curve between | and the moving target radial velocity is shown in fig. 2, when the moving target radial velocity is greater than 0, the left false target amplitude is smaller than the right false target amplitude, and when the moving target radial velocity is smaller than 0, the left false target amplitude is larger than the right false target; after the radial velocity direction is determined, fitting a curve:
wherein, anIs | AleftPolynomial fitting coefficient of |, bnIs | ArightThe polynomial fitting coefficient of | n is an integer, and the amplitude | A of the left and right false targets closest to the real target is measuredleftI and | ArightConstructing a cost function:
estimating radial velocity of moving target by gradient descent method
And further obtaining the phase error of the ith channel:
step S4: performing inverse imaging, inversely transforming the coarse imaging image domain of each group of moving targets and the corresponding false targets to an echo domain based on the inverse process of a linear frequency modulation and scaling algorithm and a spectral reconstruction algorithm, respectively compensating the phase error between channels of each moving target, and obtaining a fine imaging result of each moving target by adopting the spectral reconstruction algorithm and the linear frequency modulation and scaling algorithm;
if the residual false target still exists in the fine imaging result, iteratively performing the step S3 and the step S4 according to the amplitude of the residual false target until the false target in the fine imaging result is invisible;
the estimated moving target radial velocity is determined by the error between the measured false target amplitude and the theoretical value due to the influence of target defocusing, clutter and noise
And phase error
Errors exist, so that residual false targets possibly exist in the imaging result; and (5) performing loop iteration on the steps S3 and S4, and further estimating the residual moving target radial speed and phase error according to the residual false target amplitude until the false target in the fine imaging result is invisible.
Step S5: and superposing the fine imaging results of all the moving targets and the rough imaging results of the sea clutter to obtain a final imaging result without false targets.
The effect of the present invention is further explained by satellite-borne multi-channel SAR simulation test. The simulated radar parameters are shown in table 1, and the target position and motion parameters are shown in table 2.
TABLE 1 simulation parameters of satellite-borne multi-channel SAR simulation test
TABLE 2 target position and motion parameters
Firstly, estimating the amplitude-phase error between channels based on internal calibration data, roughly imaging sea clutter and moving targets, wherein the rough imaging result is shown in fig. 3, the targets in the block are real targets of the moving targets, the other targets are false targets, grouping the moving targets and the corresponding false targets, and extracting the rough imaging result of each moving target and the corresponding false target. Then, according to the amplitude of each real target and each false target, the radial velocity of each moving target is estimated in an iterative manner, and the estimation result of the radial velocity of each moving target after iteration is shown in table 3, wherein the estimation precision is better than 0.2 m/s. And finally, compensating the phase errors among the channels introduced by the radial speed of each moving target after inverse imaging, finishing fine imaging through frequency spectrum reconstruction and a CS algorithm, and superposing the fine imaging results of all the moving targets and the rough imaging results of sea clutter to obtain a final SAR imaging result, wherein the imaging result is shown in figure 4. It can be seen that the imaging result by adopting the method provided by the invention has no azimuth blur, no false target and good imaging quality.
TABLE 3 estimation results of radial velocity of each target after iteration
Therefore, the satellite-borne multi-channel SAR moving target imaging method quantitatively constructs the relationship between the phase error introduced by the target motion and the false target amplitude, accurately estimates the inter-channel phase error introduced by the target motion, realizes effective suppression of the false target, improves the imaging quality and makes up the defects of the prior art.
The above description is only for the purpose of describing the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention, and any variations and modifications made by those skilled in the art based on the above disclosure are within the scope of the appended claims.
Claims (6)
1. A satellite-borne multi-channel SAR moving target imaging method is characterized by comprising the following steps:
step S1: estimating inter-channel amplitude and phase errors based on the internal calibration data, compensating the inter-channel amplitude and phase errors introduced by hardware differences, and performing coarse imaging on sea clutter and moving targets by adopting a frequency spectrum reconstruction algorithm and a linear frequency modulation and scaling algorithm;
step S2: detecting moving targets and false targets in the coarse imaging by adopting a constant false alarm detection method, and grouping the detected moving targets and the false targets according to the position relation between the real target of the moving target and the false targets;
step S3: establishing a quantitative relation among inter-channel phase errors caused by moving target motion, false target amplitudes and moving target motion speeds, respectively estimating the inter-channel phase errors of each moving target, and respectively obtaining estimated values of the inter-channel phase errors of each moving target according to the measured false target amplitudes;
step S4: performing inverse imaging, inversely transforming the coarse imaging image domain of each group of moving targets and the corresponding false targets to an echo domain based on the inverse process of a linear frequency modulation and scaling algorithm and a spectral reconstruction algorithm, respectively compensating the phase error between channels of each moving target, and obtaining a fine imaging result of each moving target by adopting the spectral reconstruction algorithm and the linear frequency modulation and scaling algorithm;
step S5: and superposing the fine imaging results of all the moving targets and the rough imaging results of the sea clutter to obtain a final imaging result without false targets.
2. The on-board multi-channel SAR moving target imaging method of claim 1, wherein if there is still residual false target in the fine imaging result obtained in step S4, after step S4, before step S5, further comprising step S41:
step S41: and (4) according to the amplitude of the residual false target, iteratively performing the steps S3 and S4 until the false target in the fine imaging result is invisible.
3. The on-board multi-channel SAR moving target imaging method as claimed in claim 1 or 2, characterized in that in step S2, each set includes a real target of a moving target and a corresponding false target.
4. The on-board multi-channel SAR moving-target imaging method according to claim 3, characterized in that in step S2, the grouping is performed by:
step S21: dividing all detected targets at the same range gate into a large group;
step S22: determining the unmarked target with the strongest energy in the large group as a real target of a certain moving target;
step S23: determining false targets, wherein Nc-1 false targets are respectively determined at two ends of a real target along the azimuth direction, and the azimuth time interval between the adjacent real target and the false target is
Wherein the content of the first and second substances,
NcPRF is the pulse repetition frequency of the single-channel signal, fdrAdjusting the frequency for Doppler;
obtaining a false target corresponding to the real target;
step S24: grouping the certain moving target and the obtained corresponding false target into a group; and are
Marking the certain moving target and the corresponding false target;
step S25: iterating the above steps S22-S24 until all moving objects in the large group are traversed;
step S26: the next range gate is selected and the above steps S21 to S25 are iterated, completing the grouping in step S2.
5. The on-board multi-channel SAR moving target imaging method of claim 4, characterized in that all detected targets comprise different moving targets and their false targets.
6. The on-board multi-channel SAR moving-target imaging method according to claim 5, characterized in that after step S2, before step S3, the method further comprises the following steps:
and extracting a coarse imaging result of each moving target and the corresponding false target.
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| CN117572367B (en) * | 2024-01-15 | 2024-03-15 | 中国科学院空天信息创新研究院 | Satellite-borne azimuth multichannel ScanSAR false target simulation method |
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