A group phase shift correction method for adaptive iterative phase spectrum compensation

Abstract

The present application relates to a group phase shift correction method for adaptive iterative phase spectrum compensation. The method comprises: defining any one channel in a multi-channel system as a reference channel, and defining the remaining channels to be corrected as auxiliary channels; performing coarse focusing imaging on the echoes of the reference channel and the auxiliary channel, and then performing interference processing on the two channel data along the trajectory to obtain an interference phase spectrum; performing azimuth IFFT processing on the interference phase spectrum to obtain a main lobe phase spectrum; extracting the interference phase component matrix from the main lobe phase spectrum, performing rotation median filtering and unwrapping processing on the interference phase component matrix to obtain an unwrapped phase; performing linear fitting on the unwrapped phase to obtain a group phase shift phase history, compensating the auxiliary channel data, and iterating the group phase shift phase history. When the slope of the fitted group phase shift history approaches zero, the iteration is stopped to complete the group phase shift correction. The use of this method can improve the accuracy of group phase shift correction.

Description

Technical Field

[0001] The present application relates to the field of radar technology, and in particular to a group phase shift correction method for adaptive iterative phase spectrum compensation. Background Art

[0002] Synthetic Aperture Radar (SAR) is a high-resolution remote sensing observation technology suitable for all-day and all-weather conditions. When using SAR for Ground Moving Target Indication (GMTI), due to motion mismatch, the moving target of interest will usually have smearing, misalignment and other phenomena in a well-focused image, or even be submerged in the echo (clutter) spectrum of the ground stationary target and cannot be distinguished. Airborne single-channel SAR is limited by the number of channels and can only detect fast-moving targets whose Doppler shift is outside the clutter bandwidth. Multiple receiving channels can be set at a certain interval along the aircraft track, and the multi-channel spatial characteristics can be used to achieve clutter suppression, extract moving targets at the edge of the clutter or submerged in the clutter spectrum, and improve the target signal-to-clutter ratio. The premise of clutter suppression is to ensure that the channels have been registered, that is, it is necessary to maintain a good correlation between the channels. Ideally, the carrier aircraft flies at a constant speed along the predetermined track, there is no channel error between channels, and the echoes received by each channel only differ by an azimuth delay; but in reality, due to external uncontrollable factors such as atmospheric turbulence and mechanical control, the carrier aircraft may yaw, pitch and other movements, resulting in phase errors in the data between channels. One manifestation of this is that when the channels are interfered along the trajectory, the interference phase fringes will be significantly tilted, resulting in a group phase shift phenomenon.

[0003] At present, some people have proposed a calibration method based on attitude data measured by inertial navigation and a set of known static corner reflectors (strong scatterers) as references. The inertial navigation data obtained by the carrier flight compensates the inter-channel error, or the calibration body echo within the SAR observation range is used to extract error information to estimate the yaw and pitch of the carrier for phase correction. Some people have also proposed a two-dimensional blind calibration method, which divides a set of interferometric phase data into multiple groups along the azimuth direction, sorts the interferometric phase of each distance unit in each group of data, takes the median operation, and iterates. When the mean and standard deviation are less than the threshold, the iteration is stopped, the group phase shift is solved, and the phase is compensated by subtracting the estimated group phase shift. There is also a method that converts the interferometric phase data into a polar coordinate format through interpolation operation, constructs a two-dimensional filter to estimate the group phase shift, and subtracts the estimated background phase from the original phase data to achieve phase correction. Some people have also proposed a method of estimating the interferometric phase slope and phase offset line by line in the interferometric phase data to achieve group phase shift correction and phase slope correction in one step. In addition, some people have proposed a two-step calibration method to correct the group phase shift, that is, to correct the scene center phase error and the residual distance change phase error twice. However, the above five methods all have certain disadvantages, the main disadvantages include: a calibration method based on inertial navigation measurement attitude data and a set of known stationary corner reflectors (strong scatterers) as references: subject to prior information such as inertial navigation information and reference calibration bodies, when the inertial navigation information is inaccurate or there is no calibration body in the scene, phase correction is difficult to perform; two-dimensional blind calibration method: subject to the number of segmentation groups, when the number of segmentation groups does not match the interference phase interval, the performance drops rapidly, and the number of groups and group lengths are manually controlled; interpolation operation: it is subject to the interpolation rate and filter size selection. When the filter size is not selected appropriately, the interference phase will be destroyed; a method for estimating the interference phase slope and phase offset line by line in the interference phase data: the phase slope and offset estimation process is affected by phase noise, and large noise fluctuations will cause inaccurate phase estimation and poor correction effect; two-step calibration method, but it still requires angle prior or needs to estimate the slope from the interference phase map, and inaccurate slope estimation causes phase correction errors to accumulate. Summary of the invention

[0004] Based on this, it is necessary to provide a method for adaptively completing group phase shift correction in phase data interfered by noise without the need for crab angle priors or the existence of inertial navigation information, and only through interferometric phase data, in order to solve the above technical problems. This method is a group phase shift correction method for adaptive iterative phase spectrum compensation that ensures good correlation between channels.

[0005] A group phase shift correction method for adaptive iterative phase spectrum compensation, the method comprising:

[0006] Define any channel in the multi-channel system as a reference channel, and define the remaining channels to be calibrated as auxiliary channels;

[0007] After the echoes of the reference channel and the auxiliary channel are coarsely focused and imaged, the data of the two channels are interferometrically processed along the trajectory to obtain the interference phase spectrum;

[0008] The interference phase spectrum is processed by IFFT in azimuth to obtain the main lobe phase spectrum; the interference phase component matrix is ​​extracted from the main lobe phase spectrum, and the interference phase component matrix is ​​processed by gyration median filtering and de-wrapping to obtain the de-wrapped phase;

[0009] The phase after unwrapping is linearly fitted to obtain the phase history of the group phase shift, the auxiliary channel data is compensated, and the phase history of the group phase shift is iteratively processed. When the slope of the fitted group phase shift history tends to zero, the iteration is stopped to complete the group phase shift correction.

[0010] The above-mentioned group phase shift correction method of adaptive iterative phase spectrum compensation, this application divides the channels in the multi-channel system into reference channels and auxiliary channels, and only uses the echo data of the two channels for processing, and does not rely on prior information such as inertial navigation information and reference calibration bodies, successfully solves the problem that phase correction cannot be performed due to inaccurate inertial navigation or no calibration body, and realizes the real blind calibration of channel phase error. Then, the reference channel and auxiliary channel echoes are sequentially subjected to coarse focusing imaging, along-track interference processing, azimuth IFFT processing, etc., and correction is completed based on data characteristics and mathematical operations, avoiding the influence of factors such as artificial control of the number of segmentation groups on the correction effect, and adopts rotation median filtering when processing the interference phase component matrix to suppress noise. Finally, linear fitting and iterative processing are performed, and the iteration is stopped when the slope of the group phase shift process tends to zero. The slope can be accurately estimated under noise interference, and group phase shift correction is realized, overcoming the disadvantage of poor correction effect caused by phase noise in the line-by-line estimation method, effectively compensating for the phase error of the data between channels, completing the group phase shift correction, ensuring good correlation between channels, and facilitating the full utilization of subsequent multi-channel data. At the same time, since no interpolation is required, the interference phase is avoided from being destroyed due to improper selection of interpolation-related parameters, further ensuring channel correlation. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a schematic flow chart of a group phase shift correction method of adaptive iterative phase spectrum compensation in one embodiment;

[0012] Figure 2 A schematic diagram of a geometric model of SAR imaging of a stationary target under an ideal condition in one embodiment;

[0013] Figure 3 Schematic diagram of the relative position distribution of the actual channel and the point target in the scene when a crab angle exists in one embodiment. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0015] In one embodiment, Figure 1 As shown, a group phase shift correction method for adaptive iterative phase spectrum compensation is provided, comprising the following steps:

[0016] Step 102, define any one channel in the multi-channel system as a reference channel, and define the remaining channels to be corrected as auxiliary channels; perform coarse focusing imaging on the echoes of the reference channel and the auxiliary channel, and then perform interference processing on the data of the two channels along the trajectory to obtain an interference phase spectrum.

[0017] In multi-channel SAR-GMTI, external factors cause non-ideal motion of the carrier, resulting in yaw angle and pitch angle (crab angle) between the actual track and the ideal track of the carrier, causing the interference phase between the channels to form a group phase shift, such as Figure 2 The geometric model of SAR imaging of stationary targets under ideal conditions is established as shown in the figure. When the crab angle exists, the relative position of the actual channel and the point target in the scene is as follows: Figure 3 As shown in the figure, first determine the system parameters and deduce the mechanism of group phase shift from a theoretical perspective. Taking a single-point stationary target as an example, the imaging geometric model between the airborne platform and the stationary target in the dual-channel SAR in the positive side-view mode is as follows: Figure 2 As shown. In the coordinate system, The axis represents the direction of the aircraft's speed along the track. The axis represents the ground distance direction, The axis is perpendicular to the horizontal plane and points upward. is the aircraft height, is the aircraft speed, single point target lie in Place. Figure 2 In the example, two channels are set along the track direction. The first channel transmits and receives signals, and the second channel only receives signals. The radar transmits signals through the transmit channel, and the two channels receive signals, which can be equivalent to transmitting and receiving signals at two equivalent phase centers. After the channel positions are equivalent, the channel spacing becomes half of the original. The subsequent analysis is performed by default with two equivalent phase centers as two channels. At this time, the equivalent channel spacing is , Indicates The instantaneous slant distance of each channel.

[0018] SAR usually transmits a linear frequency modulated (LFM) pulse signal as shown in formula (1):

[0019] (1)

[0020] In the formula, is a rectangular window function, when hour, is 1; when hour, is 0. Indicates fast time, is the pulse width, is the center frequency, It is the frequency modulation of the transmitting signal.

[0021] Set up After the channel echo signal is demodulated by Dechirp and the residual video phase is removed, it is expressed as:

[0022] (2)

[0023] In the formula, is the echo signal amplitude, is the speed of light, Represents the slow time component. is the equivalent fast time. is the radar echo delay, is the distance from the radar to the reference point, is the delay corresponding to the reference distance. Expressed as the instantaneous slope distance difference relative to a reference point.

[0024] The echo signal received by Dechirp is subjected to range-direction FFT to achieve range-direction pulse compression. The signal expression is as follows:

[0025] (3)

[0026] In the formula, is the distance-wise Singer envelope, represents the distance frequency, is the wavelength.

[0027] From (3), we can see that Determines the phase term of the Dechirp received echo signal. is a constant, so the instantaneous slope distance determines the phase term. Therefore, combined with Figure 2 , based on the Taylor series, Approximately expanded to The high-order polynomial of is as follows:

[0028] (4)

[0029] In the formula, represents the zero Doppler slant range, Indicates The baseline length of each channel. Substituting equation (4) into equation (3), the signal after range pulse compression can be expressed as:

[0030] (5)

[0031] In the formula, One of the terms is a constant phase term.

[0032] Due to the inertia of the carrier aircraft, it can be considered that the crab angle is a constant in a short synthetic aperture time. Assuming that the yaw angle is , the pitch angle is Assuming that the position of channel 1 remains unchanged and the movement of the carrier only changes the position of channel 2, that is, channel 1 is defined as the reference channel and channel 2 is defined as the auxiliary channel, then the actual channel position distribution at a certain slow time moment is as follows: Figure 3 shown.

[0033] Figure 3 shows the projection of the motion error onto the pitch plane, , The corresponding yaw angles are , the pitch angle is The projection of channel 2 caused by Axis and The motion error on the axis. Both can be expressed as:

[0034] (6)

[0035] pass Figure 3 Geometric structure, the projection component of the channel 2 position error on the Doppler slant range can be expressed as:

[0036] (7)

[0037] From the above formula, we can see that Follow-down perspective Change. Bottom view It can be expressed as:

[0038] (8)

[0039] In the formula, represents the slant distance corresponding to the point target in different scenes. Combining equations (7) and (8), we can know that: Varies with distance.

[0040] Since the range pulse compression can be completed through the range FFT, it can be known that there is a one-to-one correspondence between the range frequency and the distance:

[0041] (9)

[0042] It can be considered The frequency varies with the distance. Therefore, the error term of equation (7) is introduced into equation (5), and the azimuth FFT is performed using the stationary phase principle to obtain:

[0043] (10)

[0044] (11)

[0045] In the formula, , is the synthetic aperture time. Performing ATI processing on equations (10) and (11) and taking only the interference phase term yields:

[0046] (12)

[0047] Wherein, the first term is the phase slope term, which is the phase term of the Doppler change caused by the length of the baseline along the track, and is not the focus of this paper. The second term is the phase shift term of the analyzed group, that is, the phase term to be corrected.

[0048] In the present application, any one channel in a multi-channel system is defined as a reference channel, and the remaining channels to be corrected are defined as auxiliary channels; the echoes of the reference channel and the auxiliary channel are coarsely focused and imaged, and then the two-channel data are interfered along the trajectory to obtain an interference phase spectrum, which can eliminate the influence of the interference phase azimuth slope and noise components on the subsequent group phase shift estimation. At the same time, any one channel in the multi-channel system is defined as a reference channel, and the rest are auxiliary channels, and only the echo data of the reference channel and the auxiliary channel are processed. In the whole process, there is no need to rely on prior information such as inertial navigation information and reference calibration bodies, which avoids the problem of being unable to perform phase correction due to inaccurate inertial navigation information or the absence of a calibration body in the calibration method based on inertial navigation measurement and reference calibration bodies, and achieves true blind calibration of channel phase errors.

[0049] Step 104, perform azimuth IFFT processing on the interference phase spectrum to obtain a main lobe phase spectrum; extract the interference phase component matrix from the main lobe phase spectrum, perform gyration median filtering and dewrapping processing on the interference phase component matrix to obtain the dewrapped phase.

[0050] The echoes of the reference channel and the auxiliary channel are subjected to coarse focusing imaging, interferometric processing along the trajectory, IFFT processing in azimuth, extraction of the interference phase component matrix, and gyration median filtering and dewrapping processing, and finally linear fitting and iterative processing. The entire process is based on the characteristics of the data itself and mathematical operations, and is not subject to factors such as artificial control of the number of segmentation groups. There will not be the problem of rapid performance degradation caused by the mismatch between the number of segmentation groups and the interference phase interval in the two-dimensional blind calibration method.

[0051] Step 106, linear fitting is performed on the unwrapped phase to obtain a group phase shift phase history, the auxiliary channel data is compensated, and the group phase shift phase history is iteratively processed. When the slope of the fitted group phase shift history approaches zero, the iteration is stopped to complete the group phase shift correction.

[0052] When processing the interference phase component matrix, the gyration median filter is used to effectively suppress the influence of noise on the phase data. When the unwrapped phase is subsequently linearly fitted and iteratively processed, the iteration is stopped when the slope of the fitted group phase shift process tends to zero. The iterative method based on data characteristics can accurately estimate the slope under the influence of noise, thereby realizing group phase shift correction, avoiding the problem of inaccurate phase estimation and poor correction effect caused by phase noise fluctuations in the line-by-line estimation of interference phase slope and phase offset methods. Through the above series of processing, the group phase shift correction is completed, so that the phase error of the data between channels is effectively compensated. Accurate phase correction ensures good correlation between channels, which is conducive to the full utilization of subsequent multi-channel data, unlike other methods that may not be able to improve the correlation between channels well due to inaccurate phase correction or other factors. At the same time, the entire processing process does not require interpolation, which avoids the damage to the interference phase caused by improper selection of interpolation rate and filter size, further ensures the correlation between channels, and greatly improves the accuracy of group phase shift correction.

[0053] In the above-mentioned group phase shift correction method of adaptive iterative phase spectrum compensation, by dividing the channels in the multi-channel system into reference channels and auxiliary channels, only the echo data of the two channels are used for processing, and the prior information such as inertial navigation information and reference calibration bodies are completely independent of each other, which successfully solves the problem that phase correction cannot be performed due to inaccurate inertial navigation or no calibration body, and realizes the real blind calibration of channel phase error. Then, the echoes of the reference channel and the auxiliary channel are subjected to coarse focusing imaging, along-track interference processing, azimuth IFFT processing, etc., and the correction is completed based on data characteristics and mathematical operations, avoiding the influence of factors such as artificial control of the number of segmentation groups on the correction effect, and using the rotation median filter to suppress noise when processing the interference phase component matrix. Finally, linear fitting and iterative processing are performed, and the iteration is stopped when the slope of the group phase shift process tends to zero. The slope can be accurately estimated under noise interference, and the group phase shift correction is realized, which overcomes the disadvantage of poor correction effect caused by phase noise in the line-by-line estimation method, effectively compensates for the phase error of the data between channels, completes the group phase shift correction, ensures good correlation between channels, and is conducive to the full utilization of subsequent multi-channel data. At the same time, since no interpolation is required, the interference phase is avoided from being destroyed due to improper selection of interpolation-related parameters, further ensuring channel correlation.

[0054] In one embodiment, performing along-track interference processing on two-channel data to obtain an interference phase spectrum includes:

[0055] The interference phase spectrum obtained by interfering the two-channel data along the trajectory is:

[0056] ;

[0057] in, represents the distance frequency, is the wavelength, is the projection component of the auxiliary channel position error on the Doppler slant range, represents the Doppler frequency, represents the equivalent channel spacing, Indicates the carrier speed, Represents an imaginary unit.

[0058] In one embodiment, performing azimuth IFFT processing on the interference phase spectrum to obtain a main lobe phase spectrum includes:

[0059] The interference phase spectrum is processed by azimuth IFFT to obtain the main lobe phase spectrum:

[0060] (13)

[0061] in, represents the slow time component, represents the distance frequency, is the wavelength, is the projection component of the auxiliary channel position error on the Doppler slant range, represents the Doppler frequency, represents the equivalent channel spacing, Indicates the carrier speed, represents the imaginary unit, is the Doppler bandwidth, Represents distance-dependent frequency-varying noise.

[0062] In one embodiment, due to the existence of the carrier aircraft motion speed, the Doppler of the stationary target will be broadened to form a clutter spectrum of a certain width, and the clutter center is located at the Doppler center. Therefore, after performing the azimuth IFFT, the clutter spectrum envelope of the phase will be converted to the sinc envelope, and the phase slope component will be converted to the azimuth delay. Therefore, it is inferred by determining through formula (13) The two parameters are: the main lobe width and the main lobe center position, and then the interference phase component matrix is ​​extracted from the main lobe phase spectrum, including:

[0063] The interference phase component matrix extracted from the main lobe phase spectrum is:

[0064] ;

[0065] in, represents the distance-frequency varying noise, represents the distance frequency, is the wavelength, is the projection component of the auxiliary channel position error on the Doppler slant range.

[0066] In one embodiment, the extracted phase component matrix is ​​subjected to a gyration median filter, which is mainly used to suppress the noise that varies with distance and frequency. Since the interference phase may exist The periodic phase ambiguity affects the subsequent linear fitting of the phase history, including:

[0067] The interference phase component matrix is ​​subjected to rotation median filtering and unwrapping processing, and the unwrapped phase is obtained as follows:

[0068] ;

[0069] in, , , is the half window length of the two-dimensional filter. Here, the window length of the two-dimensional filter is set to be consistent with the main lobe width of equation (13). represents the interference phase component matrix, m and n represents a discrete variable, is the phase unwrapping function, Represents the function for finding the angle.

[0070] In one embodiment, the group phase shift phase history is iteratively processed, and when the slope of the fitted group phase shift history tends to zero, the iteration is stopped to obtain the group phase shift correction result, including:

[0071] It is determined whether the slope of the phase history of the group phase shift tends to 0. If so, the iteration is stopped, and the group phase shift correction is completed. Otherwise, the auxiliary channel data shown in formula (11) in the dual-channel data is compensated according to the preset compensation function, and the compensated auxiliary channel data is interfered with the reference channel data in the dual-channel data again to calculate the new group phase shift phase history to complete the correction and iteration.

[0072] In a specific embodiment, group phase shift correction can usually be completed after 2 to 3 iterations. At this time, the inter-channel interference phase only has the phase slope term caused by the baseline component along the track, such as the first term in equation (12). For space-time adaptive processing, this term is required for spatial domain filtering; and for offset phase center antenna technology, this term needs to be eliminated and data subtraction is performed to complete clutter suppression.

[0073] In one embodiment, the preset compensation function is:

[0074] ;

[0075] in, represents the fitted linear phase history, Represents an imaginary unit.

[0076] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0077] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0078] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0079] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A group phase shift correction method for adaptive iterative phase spectrum compensation, characterized in that: The method comprises: Define any channel in the multi-channel system as a reference channel, and define the remaining channels to be calibrated as auxiliary channels; After the echoes of the reference channel and the auxiliary channel are coarsely focused and imaged, the data of the two channels are interferometrically processed along the trajectory to obtain the interference phase spectrum; Performing azimuth IFFT processing on the interference phase spectrum to obtain a main lobe phase spectrum; extracting an interference phase component matrix from the main lobe phase spectrum, performing gyration median filtering and dewrapping processing on the interference phase component matrix to obtain a dewrapped phase; The phase after unwrapping is linearly fitted to obtain a group phase shift phase history, the auxiliary channel data is compensated, and the group phase shift phase history is iteratively processed. When the slope of the fitted group phase shift history tends to zero, the iteration is stopped to complete the group phase shift correction.

2. The method according to claim 1, characterized in that: The two-channel data are processed along the trajectory to obtain the interference phase spectrum, including: The interference phase spectrum obtained by interfering the two-channel data along the trajectory is: in, represents the distance frequency, is the wavelength, is the projection component of the auxiliary channel position error on the Doppler slant range, represents the Doppler frequency, represents the equivalent channel spacing, Indicates the carrier speed, Represents an imaginary unit.

3. The method according to claim 1, characterized in that Performing azimuth IFFT processing on the interference phase spectrum to obtain a main lobe phase spectrum includes: The interference phase spectrum is processed by azimuth IFFT to obtain the main lobe phase spectrum: in, represents the slow time component, represents the distance frequency, is the wavelength, is the projection component of the auxiliary channel position error on the Doppler slant range, represents the Doppler frequency, represents the equivalent channel spacing, Indicates the carrier speed, represents the imaginary unit, is the Doppler bandwidth, Represents distance-dependent frequency-varying noise.

4. The method according to claim 1, characterized in that Extracting an interference phase component matrix from the main lobe phase spectrum includes: The interference phase component matrix extracted from the main lobe phase spectrum is: in, represents the distance-frequency varying noise, represents the distance frequency, is the wavelength, is the projection component of the auxiliary channel position error on the Doppler slant range.

5. The method according to claim 1, characterized in that The interference phase component matrix is ​​subjected to gyration median filtering and de-wrapping processing to obtain the de-wrapped phase, including: The interference phase component matrix is ​​subjected to rotation median filtering and unwrapping processing, and the unwrapped phase is obtained as follows: in, , , is the half window length of the two-dimensional filter, represents the interference phase component matrix, m and n represents a discrete variable, is the phase unwrapping function, Represents the function for finding the angle.

6. The method according to claim 1, characterized in that The group phase shift phase history is iterated, and when the slope of the fitted group phase shift history approaches zero, the iteration is stopped to obtain a group phase shift correction result, including: It is determined whether the slope of the group phase shift phase history tends to 0. If so, the iteration is stopped, and the group phase shift correction is completed at this time; otherwise, the auxiliary channel data in the dual-channel data is compensated according to the preset compensation function, and the compensated auxiliary channel data is interfered with the reference channel data in the dual-channel data again, and the new group phase shift phase history is calculated to complete the correction and iteration.

7. The method according to claim 6, characterized in that The preset compensation function is: in, represents the fitted linear phase history, Represents an imaginary unit.

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