CN116400310A - Two-dimensional frequency domain azimuth multi-channel SAR error correction method - Google Patents

Two-dimensional frequency domain azimuth multi-channel SAR error correction method Download PDF

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CN116400310A
CN116400310A CN202310596689.8A CN202310596689A CN116400310A CN 116400310 A CN116400310 A CN 116400310A CN 202310596689 A CN202310596689 A CN 202310596689A CN 116400310 A CN116400310 A CN 116400310A
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echo signals
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CN116400310B (en
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续宗祥
李俊峰
蔡永华
陆萍萍
杨天园
吴一戎
王宇
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Aerospace Information Research Institute of CAS
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • G01S7/4004—Means for monitoring or calibrating of parts of a radar system
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9021—SAR image post-processing techniques

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Abstract

The invention discloses a two-dimensional frequency domain azimuth multichannel SAR error correction method, which comprises the following steps: receiving echo signals of a plurality of channels, wherein the echo signals are sampled at a first pulse repetition frequency; performing amplitude error estimation and correction on the received echo signals of the channels; performing azimuth and distance fast Fourier transformation on the multichannel echo signals subjected to amplitude error correction, and transforming the two-dimensional time domain echo signals into two-dimensional frequency domain echo signals; the two-dimensional frequency domain echo signals of each channel are summed up after phase compensation to establish an L1 norm maximization optimization model; carrying out iterative solution by using a global optimal algorithm to obtain accurate phase errors and carrying out phase error correction on echo signals of all channels; reconstructing the multichannel signal sampled at the first pulse repetition frequency after the phase error correction into a single-channel echo signal sampled at the second pulse repetition frequency; and obtaining a high-resolution wide SAR image without false targets by using an imaging algorithm.

Description

Two-dimensional frequency domain azimuth multi-channel SAR error correction method
Technical Field
The invention relates to the technical field of radars, in particular to a two-dimensional frequency domain azimuth multi-channel SAR error correction method.
Background
Synthetic aperture radar (Synthetic Aperture Radar, SAR) uses synthetic aperture imaging with high resolution in azimuth. The synthetic aperture radar is used as an active remote sensor working in a microwave frequency band, is not influenced by weather and illumination conditions, can observe the ground all the time and all the weather, has certain penetrating capacity, can acquire information below the ground surface, and therefore, the synthetic aperture radar is rapidly developed in the past decades and has important application in the field of modern microwave remote sensing. In order to monitor a wider range of scene information and provide finer scene information, higher resolution and wider mapping breadth are the necessary trends in the development of the microwave remote sensing field. The azimuth multi-channel technology improves time sampling by space sampling equivalent, solves the contradiction between the azimuth high resolution and the distance wide mapping band of the traditional spaceborne SAR, and becomes one of the important systems for realizing high-resolution wide SAR imaging at present.
The azimuth multi-channel SAR system mainly adopts an offset phase center azimuth multi-beam system, and adopts a working mode of single-channel transmission and multi-channel reception by dividing an antenna into a plurality of equally-spaced sub-apertures. The azimuth multi-channel SAR system transmits a chirp signal at a low pulse repetition frequency (Pulse Repetition Frequency, PRF) and achieves an increase in range-to-swath width by increasing the length of the signal receiving window. Meanwhile, the echo signals received by each sub-aperture can be equivalently self-received echo signals in the equivalent phase center, the time sampling rate is increased by increasing the space sampling equivalent, and the PRF is ensured to meet the Nyquist sampling theorem, so that the azimuth resolution is unchanged while the distance mapping bandwidth is increased. However, the introduction of multiple channels also brings about various errors, so that system parameters are changed, the mismatch between the reconstruction filter and the multiple channels of echo signals is caused by the inconsistent channels, and fuzzy energy is introduced into the reconstructed single channel echo signals, so that the performance of the azimuth multi-channel SAR system is severely restricted. The amplitude and phase errors among the channels have the most serious influence on the reconstructed signals, so that the amplitude and phase consistency correction among the channels becomes a key link in the signal processing of the azimuth multi-channel SAR system.
In the current developed channel phase error correction method, the signal subspace method and the image domain method are mainly adopted, however, under the condition of low signal-to-noise ratio, the signal subspace and the noise subspace are difficult to separate, so that the correction performance of the method is greatly affected. In addition, the signal subspace type method needs additional redundant channels, and limits the application scene of the method. The image domain method has high estimation precision and good stability, but needs to carry out imaging processing on the multichannel signals, and estimates channel errors by processing a plurality of images, so that the calculated amount is large.
Disclosure of Invention
In order to solve the technical problems, the invention provides a two-dimensional frequency domain azimuth multi-channel SAR error correction method, wherein a sum L1 norm maximization optimization model of multi-channel echo signals is established in a two-dimensional frequency domain, a global optimization algorithm is utilized to iteratively solve channel phase errors, so that amplitude and phase errors among channels can be accurately corrected, and false targets of SAR image azimuth can be eliminated.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a two-dimensional frequency domain azimuth multi-channel SAR error correction method comprises the following steps:
step 1, receiving echo signals of a plurality of channels, and estimating and compensating amplitude errors of the received echo signals of the channels; the echo signal is sampled at a first pulse repetition frequency;
step 2, converting echo signals of a plurality of channels sampled by the first pulse repetition frequency after finishing amplitude error correction into two-dimensional frequency domain multi-channel echo signals through fast Fourier transform;
step 3, compensating phases caused by the interval distances between corresponding equivalent phase centers and phase centers of reference channels for the two-dimensional frequency domain echo signals of each channel, and summing the two-dimensional frequency domain multi-channel echo signals after compensating the phases to establish an L1 norm maximization optimization model;
step 4, carrying out iterative solution by using a global optimal algorithm to obtain accurate phase errors, and carrying out phase error correction on echo signals of all channels;
step 5, reconstructing the multichannel signal sampled at the first pulse repetition frequency after the phase error correction into a single-channel echo signal sampled at a second pulse repetition frequency, wherein the second pulse repetition frequency is higher than the first pulse repetition frequency;
and 6, obtaining a high-resolution wide SAR image without direction blurring by using a CS imaging algorithm.
Further, the step 1 includes:
carrying out azimuth Fourier transform on echo signals of a plurality of channels, taking an average value of amplitude spectrums along azimuth and distance directions, and taking the average value of the amplitude spectrums of the echo signals of the channels and the average value of the amplitude spectrums of a reference channel as a quotient to obtain amplitude error estimation; and then carrying out amplitude correction on echo signals of the channels according to the estimated amplitude errors.
Further, the step 3 includes:
and compensating a linear phase generated by an equivalent phase center interval for each channel of two-dimensional frequency domain echo signals, summing corresponding frequency points of the compensated two-dimensional frequency domain multi-channel echo signals in the azimuth direction, establishing an L1 norm maximization optimization model, and carrying out iterative solution by using a global optimization algorithm to obtain an accurate phase error.
The beneficial effects are that:
compared with the existing signal subspace method and image domain method, the method fully utilizes the sparse characteristic of the L1 norm, can show excellent estimation performance even under the condition of low signal-to-noise ratio, accurately corrects phase errors and obtains imaging results without false targets. In addition, the invention does not need to image the multichannel signals respectively, and only needs to convert the two-dimensional time domain echo signals into the two-dimensional frequency domain echo signals when estimating the channel errors, and the two-dimensional frequency domain echo signals are summed after compensating the phases, so that the calculation speed is further improved while the estimation precision is maintained.
Drawings
FIG. 1 is a flow chart of a two-dimensional frequency domain azimuth multi-channel SAR error correction method of the present invention;
FIG. 2 is a schematic diagram of a satellite-borne azimuth multi-channel SAR operating mechanism;
FIG. 3 is a graph of imaging results of GF-3 satellite dual-channel data without error correction;
FIG. 4 is a graph of the results of error correction for GF-3 satellite dual channel data.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by those skilled in the art without the inventive effort based on the embodiments of the present invention are within the scope of protection of the present invention.
According to an embodiment of the present invention, as shown in fig. 1, the two-dimensional frequency domain azimuth multi-channel SAR error correction method of the present invention comprises the following steps:
step 101: and carrying out amplitude error estimation and compensation on the received echo signals of the channels by using a channel equalization method.
The multi-channel echo signal with amplitude and phase errors is represented as follows:
Figure SMS_1
(1)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_3
and->
Figure SMS_8
Respectively represent +.>
Figure SMS_12
The flow path of the liquid is provided with a channel,two-dimensional time-domain echo signal with channel error and without channel error,>
Figure SMS_4
and->
Figure SMS_7
Respectively represent->
Figure SMS_11
Amplitude error and phase error of the channel, +.>
Figure SMS_14
And->
Figure SMS_2
Representing distance fast time and azimuth slow time, respectively, < >>
Figure SMS_6
，/>
Figure SMS_10
For the number of channels>
Figure SMS_13
Representing natural number->
Figure SMS_5
Index (I)>
Figure SMS_9
Representing imaginary units.
The channel amplitude error and the phase error of the azimuth multi-channel SAR system are mutually independent and can be corrected separately. The amplitude error between channels is generally corrected, and the amplitude error estimated value
Figure SMS_15
The method can be obtained by a channel equalization method, and firstly, azimuth fast Fourier transform is carried out on echo signals of all channels:
Figure SMS_16
(2)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_17
representing the azimuthal fast fourier transform, +.>
Figure SMS_18
Indicating Doppler frequency, ++>
Figure SMS_19
For the first pulse repetition frequency, < >>
Figure SMS_20
Indicate->
Figure SMS_21
The channel error signal over the range-doppler domain, the amplitude error estimate results are as follows:
Figure SMS_22
(3)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_23
and->
Figure SMS_24
Respectively representing the desire along the distance direction and the azimuth direction, taking the 1 st channel as the reference channel, and the +.>
Figure SMS_25
Representing the error-free signal of the reference channel over the range-doppler domain. Thus correct the +.o after amplitude error correction>
Figure SMS_26
Channel echo signal->
Figure SMS_27
The following are provided:
Figure SMS_28
(4)
step 102: the multichannel signal sampled by the first pulse repetition frequency which completes the amplitude error correction is transformed into a two-dimensional frequency domain multichannel echo signal through fast Fourier transformation.
In the amplitude error correction of step 101, the multichannel echo signal has completed the azimuthal fast fourier transform, so after the amplitude error correction, the multichannel echo signal is further subjected to the distance fast fourier transform, and then there are:
Figure SMS_29
(5)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_30
the +.o. indicating completion of amplitude error correction>
Figure SMS_31
Channel two-dimensional frequency domain echo signal>
Figure SMS_32
Represents distance frequency, and is omitted in the following>
Figure SMS_33
Will->
Figure SMS_34
Simplified to->
Figure SMS_35
，/>
Figure SMS_36
Representing the distance to fast fourier transform.
Step 103: compensating phases for the echo signals of the two-dimensional frequency domains of all channels, and summing to establish an L1 norm maximization optimization model;
a schematic diagram of the azimuth multi-channel SAR operating mechanism is shown in fig. 2, wherein,
Figure SMS_37
indicating the most recent pitch of the circle,
Figure SMS_38
indicating the skew history between the transmit aperture and the target,/->
Figure SMS_39
Indicate->
Figure SMS_40
The skew between the individual receive apertures to the target,/->
Figure SMS_41
Indicate->
Figure SMS_42
Skew history between the center of each equivalent phase and the target,/->
Figure SMS_43
Representing the spacing between adjacent apertures, having a length of 4.9m; the first pulse repetition frequency is PRF. Taking an azimuthal dual-channel SAR as an example, setting the first channel as a reference channel, the matrix form of the error-free multi-channel received signal represents:
Figure SMS_44
(6)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_47
no. I representing the aliasing free spectrum of the reference channel>
Figure SMS_50
Sub-band, < >>
Figure SMS_53
Which is indicative of the velocity of the satellite,
Figure SMS_46
is a system pre-filter matrix,/->
Figure SMS_49
Represents the 1 st subband, ">
Figure SMS_51
Indicate->
Figure SMS_52
A sub-band. />
Figure SMS_45
Indicate->
Figure SMS_48
Length of interval between each channel and reference channel:
Figure SMS_54
(7)
the azimuth frequency domain echo signal expression of each channel can be known from the expression (6) as follows:
Figure SMS_55
(8)
Figure SMS_56
(9)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_58
first +.>
Figure SMS_60
The frequency points of the frequency spectrum are selected,
Figure SMS_62
,/>
Figure SMS_59
indicating the number of azimuthal sampling points at the first pulse repetition frequency,/for>
Figure SMS_61
And->
Figure SMS_63
Respectively representing the 1 st sub-band and the 2 nd sub-bandBand->
Figure SMS_64
Frequency points. Thus, compensating the echo signal of the second channel for phase +.>
Figure SMS_57
Obtaining:
Figure SMS_65
(10)
at this time, an L1 norm model of the sum of two-dimensional frequency domain multi-channel echo signals can be established
Figure SMS_66
：
Figure SMS_67
(11)
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_68
is the channel phase error estimate for the second channel. Then an L1 norm maximization optimization model is built:
Figure SMS_69
(12)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_70
express +.>
Figure SMS_71
Maximized estimated phase error +.>
Figure SMS_72
。
Step 104: the global optimization algorithm is utilized to carry out iterative solution to obtain accurate phase errors, and the phase errors of echo signals of all channels are corrected;
to use the global optimization algorithm, the maximization model of equation (12) is rewritten as:
Figure SMS_73
(13)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_74
express +.>
Figure SMS_75
Minimized estimated phase error +.>
Figure SMS_76
. Obtaining a phase error estimate by using a global optimization algorithm>
Figure SMS_77
The phase error correction for the second channel is as follows:
Figure SMS_78
(14)
step 105: reconstructing the multichannel signal sampled at the first pulse repetition frequency after the phase error correction into a single-channel echo signal sampled at a second pulse repetition frequency, wherein the second pulse repetition frequency is higher than the first pulse repetition frequency;
first by distance inverse fast fourier transform
Figure SMS_79
Converting the two-dimensional frequency domain channel echo signals into range-doppler domain echo signals:
Figure SMS_80
(15)
using reconstruction filter matrices according to multichannel signal reconstruction techniques
Figure SMS_81
And carrying out reconstruction processing on the multichannel received signal subjected to channel error compensation:
Figure SMS_82
(16)
Figure SMS_83
(17)
Figure SMS_84
(18)
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_86
and->
Figure SMS_89
Representing the reconstructed second pulse repetition frequency sampled single-channel echo signal and the channel error corrected first pulse repetition frequency sampled multi-channel echo signal matrix respectively.
Figure SMS_92
，/>
Figure SMS_87
Representing reconstruction Filter matrix->
Figure SMS_90
Is>
Figure SMS_91
Row vector->
Figure SMS_93
Representing a transmission matrix filter->
Figure SMS_85
Representing the Doppler frequency after reconstruction, < >>
Figure SMS_88
。
Step 106: and obtaining the high-resolution wide SAR image without the direction blurring by using a CS imaging algorithm.
The final imaging work can be completed by selecting a single-channel signal imaging algorithm, and the invention adopts CS imagingLike an algorithm. Let the system function of CS algorithm imaging process be
Figure SMS_94
The following steps are:
Figure SMS_95
(19)
Figure SMS_96
i.e. the finally obtained high resolution wide SAR image without direction blurring.
Example 1
In the embodiment, star-high-resolution No. three (GF-3) satellite dual-channel actual measurement data are selected for processing, and the scene image is acquired on 13 days of 3 months in 2018 and is positioned in a pig seedling lagoon area in the northwest direction of mountain city in Japanese county.
Fig. 3 shows the imaging results without error correction. Wherein the ghosts in the upper and lower boxes of fig. 3 are generated by the object in the middle box. The azimuth blurring in the image is very serious, the real pig-raising lake is submerged by the false target, and the two false targets generated by the pig-raising lake submerge the original real target.
Fig. 4 shows the results after correction by the algorithm of the present invention. The amplitude and phase errors of the channel 2 relative to the channel 1 estimated by the algorithm of the invention are-0.4257 dB and-0.4257 dB respectively
Figure SMS_97
. It can be seen that the azimuth ambiguity in fig. 3 has almost completely disappeared and false objects are effectively suppressed.
The foregoing is merely a few examples of the present invention, and the present invention is applicable in other situations and is not intended to limit the scope of the present invention.

Claims (3)

1. A two-dimensional frequency domain azimuth multi-channel SAR error correction method is characterized by comprising the following steps:
step 1, receiving echo signals of a plurality of channels, and estimating and compensating amplitude errors of the received echo signals of the channels; the echo signal is sampled at a first pulse repetition frequency;
step 2, converting echo signals of a plurality of channels sampled by the first pulse repetition frequency after finishing amplitude error correction into two-dimensional frequency domain multi-channel echo signals through fast Fourier transform;
step 3, compensating phases caused by the interval distances between corresponding equivalent phase centers and phase centers of reference channels for the two-dimensional frequency domain echo signals of each channel, and summing the two-dimensional frequency domain multi-channel echo signals after compensating the phases to establish an L1 norm maximization optimization model;
step 4, carrying out iterative solution by using a global optimal algorithm to obtain accurate phase errors, and carrying out phase error correction on echo signals of all channels;
step 5, reconstructing the multichannel signal sampled at the first pulse repetition frequency after the phase error correction into a single-channel echo signal sampled at a second pulse repetition frequency, wherein the second pulse repetition frequency is higher than the first pulse repetition frequency;
and 6, obtaining a high-resolution wide SAR image without direction blurring by using a CS imaging algorithm.
2. The method for correcting two-dimensional frequency domain azimuth multi-channel SAR error according to claim 1, wherein said step 1 comprises:
carrying out azimuth Fourier transform on echo signals of a plurality of channels, taking an average value of amplitude spectrums along azimuth and distance directions, and taking the average value of the amplitude spectrums of the echo signals of the channels and the average value of the amplitude spectrums of a reference channel as a quotient to obtain amplitude error estimation; and then carrying out amplitude correction on echo signals of the channels according to the estimated amplitude errors.
3. The method for correcting two-dimensional frequency domain azimuth multi-channel SAR error according to claim 2, wherein said step 3 comprises:
and compensating a linear phase generated by an equivalent phase center interval for each channel of two-dimensional frequency domain echo signals, summing corresponding frequency points of the compensated two-dimensional frequency domain multi-channel echo signals in the azimuth direction, establishing an L1 norm maximization optimization model, and carrying out iterative solution by using a global optimization algorithm to obtain an accurate phase error.
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