Channel phase deviation correction method and system of multi-channel SAR (Synthetic Aperture Radar)

Abstract

The invention provides a channel phase deviation correction method and system for a multi-channel SAR. The method comprises the following steps: inputting azimuth multi-channel SAR echo data; performing distance compression on the echo data of each channel; calculating a correlation coefficient between instantaneous adjacent channels and an optimal correlation coefficient between adjacent azimuth moment channels; estimating Doppler center frequency in a self-adaptive weighted manner; inverting the phase deviation between channels by using the Doppler center frequency; correcting the echo or imaging data with the phase deviation; and outputting the corrected data. According to the method, only the statistical characteristics of the echo data are utilized, an external calibration source is not needed, the precision and robustness of phase deviation estimation are remarkably improved, the problem of channel mismatch in an interlaced pulse repetition interval mode is effectively solved, and a reliable technical basis is provided for high-resolution wide swath imaging and moving target detection.

Description

Technical Field

[0001] This invention relates to the field of synthetic aperture radar signal processing technology, specifically to a channel phase deviation correction method and system for multi-channel SAR, and more particularly to a channel phase deviation correction method suitable for interleaved pulse repetition interval azimuth multi-channel SAR. Background Technology

[0002] Azimuth multichannel SAR technology is an effective way to achieve high-resolution, wide-swathe imaging, but its performance is limited by the phase inconsistency between the receiving channels. This phase deviation, introduced by hardware differences, destroys signal coherence, leading to decreased image quality and failure of advanced applications. Especially when using complex modes such as staggered pulse repetition interval (PRI), the spatiotemporal relationship of the signal becomes more complex, making the phase error problem even more prominent. Traditional correction methods rely on external calibrators or manual point target selection, which is cumbersome and difficult to process in real time, severely restricting the practical development of multichannel SAR systems. Therefore, researching inter-channel phase deviation estimation techniques suitable for staggered pulse interval azimuth multichannel SAR has significant theoretical and applied value, and can overcome the fundamental contradiction between resolution and swathe width in traditional single-channel SAR systems.

[0003] The Space-Time Cross-Correlation Coefficient (STCCC) algorithm proposed in the paper "On the Baseband Doppler Centroid Estimation for Multichannel HRWS SAR Imaging" (Yanyang Liu et al., IEEE Geosciene and Remote Sensing Letters, Vol. 11, No. 12, 2014) fully utilizes the correlation between channels to estimate the phase deviation between channels while effectively estimating the azimuth multichannel SAR baseband Doppler center. However, the STCCC method is only effective in the fixed pulse repetition period (PRF) mode. Its assumption based on fixed spatiotemporal relationships no longer holds in interleaved PRF systems, leading to phase estimation errors or even failure.

[0004] The paper "Robust Channel Phase Error Calibration Algorithm for Multichannel High-Resolution and Wide-Swath SAR Imaging" (L. Zhang, Y. Gao and X. Liu, IEEE Geoscience and Remote Sensing Letters, vol. 14, no. 5, pp. 649-653) proposes a robust channel phase error calibration algorithm based on maximizing the output power of a minimum variance distortionless response (MVDR) beamformer. Under accurate steering vectors, the output power of the MVDR beamformer reaches its maximum. This method directly seeks the phase error estimate that maximizes the MVDR output power by constructing an optimization problem, without the eigenvalue decomposition required by traditional subspace methods. It uses the inverse of the covariance matrix and the nominal steering vector to construct the optimization function, thereby estimating the channel phase error. Although this method avoids subspace decomposition and does not require channel redundancy, its performance depends on accurate estimation of the covariance matrix, which requires a sufficient number of range-Doppler cell samples. In situations with low signal-to-noise ratios or unclear scene features, the estimation of the covariance matrix may be inaccurate, thus affecting the accuracy of phase error estimation. However, this method is only effective in the fixed PRF mode; its assumption based on fixed spatiotemporal relationships will no longer hold in the interleaved PRI system, leading to phase estimation bias or even failure.

[0005] The paper "A Novel Channel Errors Calibration Algorithm for Multichannel High-Resolution and Wide-Swath SAR Imaging" (H. Huang et al., IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-19) proposes a channel error calibration algorithm for multichannel high-resolution wide-swath synthetic aperture radar (HRWS-SAR) based on orthogonal projection theory. This method first estimates and compensates for range synchronization time errors using total least squares (TLS) technology, then calibrates amplitude errors using local cross-correlation, and finally estimates and compensates for inter-channel phase errors in the Doppler domain by constructing orthogonal projection weight vectors with the criterion of maximizing total output power. This algorithm avoids the covariance matrix eigenvalue decomposition in traditional subspace methods, thus reducing signal leakage under low signal-to-noise ratio (SNR) conditions and improving the robustness and accuracy of error estimation. However, this method is only effective in fixed PRF mode; its assumption based on fixed spatiotemporal relationships no longer holds in interleaved PRI systems, leading to phase estimation deviations or even failure.

[0006] Patent application CN202411215283.1 discloses a multi-channel error correction method and related device for a spaceborne SAR system. This method involves deploying equipment capable of transmitting linear frequency modulated pulse signals in a specific external calibration field. When a satellite passes overhead, the system acquires the signal of a known point target in pure receiving mode. On the ground, the absolute time delay and phase deviation of each channel relative to the reference signal are directly calculated by performing deskewing and differentiation operations on the echo, thus obtaining accurate amplitude and phase compensation coefficients. However, this method relies on a fixed PRF (Pressure Frequency Response), which no longer holds true in interleaved PRI (Pressure Frequency Response) systems, leading to the failure of phase deviation estimation.

[0007] Patent application CN202310770895.6 discloses a method for estimating phase error in oblique-looking multi-channel SAR based on subspace orthogonality. It provides a subspace orthogonality method based on eigenvalue decomposition, estimating phase error by comparing the data-driven signal subspace and the model-driven steering vector subspace. However, this method assumes a fixed PRF (Pressure Flow Factor), which no longer holds in interleaved PRI (Pressure Flow Factor) systems, leading to phase estimation errors and failure.

[0008] Patent application CN202310995946.5 discloses a phase error correction method for azimuth multi-channel SAR based on minimum spectral difference. This method estimates phase error by optimizing the difference in spectral discontinuities, and is an iterative optimization method based on spectral continuity. Its limitations include the need for iterative optimization, computational efficiency bottlenecks, and the potential introduction of errors in the pre-reconstruction process. Furthermore, this method assumes a fixed PRF (Pressure Response Factor), which no longer holds in interleaved PRI (Primary Spectrum Interference) systems, leading to phase estimation errors and failure.

[0009] In summary, the fixed PRF model assumption of traditional multi-channel SAR channel phase deviation correction methods limits their applicability and makes them difficult to apply to inter-channel amplitude and phase deviation correction in azimuth multi-channel SAR with staggered pulse repetition intervals. Addressing the shortcomings of existing technologies, this invention, for the first time, analyzes and solves the problem of inter-channel phase deviation estimation applicable to staggered pulse interval azimuth multi-channel SAR, breaking through the technical bottleneck of traditional methods in inter-channel phase deviation estimation for staggered pulse interval azimuth multi-channel SAR, and providing reliable technical support for achieving high-resolution SAR imaging. Summary of the Invention

[0010] In view of the deficiencies in the prior art, the purpose of this invention is to provide a channel phase deviation correction method and system for multi-channel SAR.

[0011] A channel phase deviation correction method for multi-channel SAR provided by the present invention includes the following steps: Step S1: Acquire raw echo data of interleaved pulse repetition interval azimuth multichannel SAR; Step S2: Perform range compression processing on the raw echo data of each channel obtained in step S1 to obtain the range-compressed echo data of each channel; Step S3: Based on the distance-compressed echo data of each channel obtained in Step S2, estimate the correlation coefficient between adjacent channels at instantaneous times and the optimal correlation coefficient between channels at adjacent azimuth times; Step S4: Combining the instantaneous correlation coefficient between adjacent channels obtained in Step S3 and the optimal correlation coefficient between channels at adjacent azimuth times, perform adaptive weighted estimation of the Doppler center frequency; Step S5: Based on the Doppler center frequency estimation results obtained in step S4, the phase deviation values ​​between each channel are obtained by inversion; Step S6: Using the inter-channel phase deviation value obtained from step S5, perform phase correction processing on the range-compressed echo data or the imaging data generated based on the echo data in step S2. Step S7: Output the echo data or imaging data after phase deviation correction in step S6 to complete the entire inter-channel phase deviation estimation and correction process.

[0012] Preferably, step S3 specifically includes the following steps: Step S3.1: Estimate the correlation coefficient between instantaneously adjacent channels. The estimation expression for the correlation coefficient between instantaneously adjacent channels is:

[0013] in, Indicates location and time The correlation coefficient between the m-th receiving channel and the (m+1)-th receiving channel; Indicates location and time The distance to the sampling point at the nth sampling point of the mth receiving channel after compression; Indicates location and time The distance to the nth sampling point in the (m+1)th receiving channel after compression; superscript Indicates conjugate; Integers, ranging from 1 to , Indicates the total number of channels; This represents the summation of the distance-compressed signals at all distance sampling points in the receiving channel; Step S3.2: Estimate the optimal correlation coefficient between channels at adjacent azimuth times, and define the azimuth time. No. Each channel and orientation time No. If the correlation coefficient of a channel is optimal, then the estimated expression for the optimal correlation coefficient between channels at adjacent azimuth times is:

[0014] in, Indicates location and time No. Each channel and orientation time No. Correlation coefficients between channels; Indicates location and time First The compressed signal at the nth distance sampling point of each receiving channel; Indicates location and time First The compressed signal at the nth distance sampling point of each receiving channel; superscript Indicates conjugate; Indicates location and time The pulse repetition interval with the next azimuth time; and Integers, ranging from 1 to , This represents the total number of channels.

[0015] Preferably, in step S3.2, the azimuth time... No. Each channel and orientation time No. The channel selection satisfies the shortest channel spatiotemporal distance, expressed as:

[0016] in, Indicates the first The first channel and the first The spatiotemporal distance of each channel; argmin|.| is the minimum value function; For the direction and time Time The three-dimensional spatial position of each channel; Indicates the direction and time as Time The three-dimensional spatial position of each channel; Indicates location and time The pulse repetition interval with the next azimuth time; and Integers, ranging from 1 to , This represents the total number of channels.

[0017] Preferably, step S4 specifically includes the following steps: Step S4.1: Estimate the instantaneous Doppler center, azimuth and time. Doppler center estimate at time for:

[0018] in, Location and time The corresponding pulse repetition frequency, where angle{·} is the argument function. This represents the optimal coherence coefficient between adjacent time channels. The multiplication symbol is used. The correlation coefficient between adjacent channels; Step S4.2: Perform weighted fusion of the Doppler centers across the entire scene, expressed as:

[0019] in, Location and time Doppler center estimate at time, Indicates time for all directions Sum the corresponding terms. Location and time The weight of the Doppler center estimate at time is calculated using the following formula:

[0020] in, Location and time The corresponding pulse repetition frequency, This represents the optimal coherence coefficient between adjacent time channels. This represents the correlation coefficient between adjacent channels.

[0021] Preferably, step S5 specifically includes the following steps: Step S5.1: Calculate the coherence coefficient of adjacent channels across the entire scene. The calculation formula is:

[0022] in, This refers to the location and time. Location and time The estimated correlation coefficient between the m-th and (m+1)-th channels; Step S5.2: Calculate the phase deviation between adjacent channels The calculation formula is:

[0023] in, Let be the full-scene correlation coefficient between the m-th and m+1-th channels. j Represents the imaginary unit. This is the estimated value of the Doppler center for the entire scene. The spatial spacing between the phase centers of adjacent channel antennas. For satellite speed; Step S5.3: Calculate the phase deviation of each channel relative to the reference channel, specifically the phase deviation between the m-th channel and the 1st channel. for:

[0024] in, This represents the phase deviation between the k-th channel and the (k+1)-th channel.

[0025] The present invention also provides a channel phase deviation correction system for multi-channel SAR, comprising the following modules: Module M1: Acquires raw echo data from interleaved pulse repetition interval azimuth multichannel SAR; Module M2: Performs distance compression processing on the raw echo data of each channel obtained in module M1 to obtain distance-compressed echo data of each channel; Module M3: Based on the distance-compressed echo data of each channel obtained from Module M2, estimate the correlation coefficient between adjacent channels at instantaneous times and the optimal correlation coefficient between channels at adjacent azimuth times; Module M4: Combining the instantaneous correlation coefficient between adjacent channels obtained from Module M3 and the optimal correlation coefficient between channels at adjacent azimuth times, an adaptive weighted estimation of the Doppler center frequency is performed; Module M5: Based on the Doppler center frequency estimation results obtained from Module M4, the phase deviation values ​​between each channel are inverted to obtain the phase deviation values. Module M6: Using the inter-channel phase deviation value obtained by inversion from module M5, perform phase correction processing on the range-compressed echo data in module M2 or the imaging data generated based on the echo data; Module M7: Outputs the phase-biased echo data or imaging data from module M6, completing the entire inter-channel phase bias estimation and correction process.

[0026] Preferably, module M3 specifically includes the following modules: Module M3.1: Estimates the correlation coefficient between instantaneously adjacent channels. The estimation expression for the correlation coefficient between instantaneously adjacent channels is:

[0027] in, Indicates location and time The correlation coefficient between the m-th receiving channel and the (m+1)-th receiving channel; Indicates location and time The distance to the sampling point at the nth sampling point of the mth receiving channel after compression; Indicates location and time The distance to the nth sampling point in the (m+1)th receiving channel after compression; superscript Indicates conjugate; Integers, ranging from 1 to , Indicates the total number of channels; This represents the summation of the distance-compressed signals at all distance sampling points in the receiving channel; Module M3.2: Estimates the optimal correlation coefficient between channels at adjacent azimuth times, defining azimuth times. No. Each channel and orientation time No. If the correlation coefficient of a channel is optimal, then the estimated expression for the optimal correlation coefficient between channels at adjacent azimuth times is:

[0028] in, Indicates location and time No. Each channel and orientation time No. Correlation coefficients between channels; Indicates location and time First The compressed signal at the nth distance sampling point of each receiving channel; Indicates location and time First The compressed signal at the nth distance sampling point of each receiving channel; superscript Indicates conjugate; Indicates location and time The pulse repetition interval with the next azimuth time; and Integers, ranging from 1 to , This represents the total number of channels.

[0029] Preferably, in module M3.2, the azimuth time... No. Each channel and orientation time No. The channel selection satisfies the shortest channel spatiotemporal distance, expressed as:

[0030] in, Indicates the first The first channel and the first The spatiotemporal distance of each channel; argmin|.| is the minimum value function; For the direction and time Time The three-dimensional spatial position of each channel; Indicates the direction and time as Time The three-dimensional spatial position of each channel; Indicates location and time The pulse repetition interval with the next azimuth time; and Integers, ranging from 1 to , This represents the total number of channels.

[0031] Preferably, module M4 specifically includes the following modules: Module M4.1: Estimates the instantaneous Doppler center, azimuth-time. Doppler center estimate at time for:

[0032] in, Location and time The corresponding pulse repetition frequency, where angle{·} is the argument function. This represents the optimal coherence coefficient between adjacent time channels. The multiplication symbol is used. The correlation coefficient between adjacent channels; Module M4.2: Performs weighted fusion of Doppler centers across the entire scene; the expression is:

[0033] in, Location and time Doppler center estimate at time, Indicates time for all directions Sum the corresponding terms. Location and time The weight of the Doppler center estimate at time is calculated using the following formula:

[0034] in, Location and time The corresponding pulse repetition frequency, This represents the optimal coherence coefficient between adjacent time channels. This represents the correlation coefficient between adjacent channels.

[0035] Preferably, module M5 specifically includes the following modules: Module M5.1: Calculates the coherence coefficient of adjacent channels across the entire scene. The calculation formula is:

[0036] in, This refers to the location and time. Location and time The estimated correlation coefficient between the m-th and (m+1)-th channels; Module M5.2: Calculates the phase deviation between adjacent channels The calculation formula is:

[0037] in, Let be the full-scene correlation coefficient between the m-th and m+1-th channels. j Represents the imaginary unit. This is the estimated value of the Doppler center for the entire scene. The spatial spacing between the phase centers of adjacent channel antennas. For satellite speed; Module M5.3: Calculates the phase deviation of each channel relative to the reference channel, and the phase deviation between the m-th channel and the 1st channel. for:

[0038] in, This represents the phase deviation between the k-th channel and the (k+1)-th channel.

[0039] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention effectively improves the fully adaptive online calibration capability, without relying on external calibration equipment or manual intervention. It can complete the calibration by utilizing only the statistical characteristics of the echo data itself, which greatly improves the engineering practicality and operation and maintenance efficiency of multi-channel SAR systems.

[0040] 2. This invention significantly enhances the estimation accuracy and robustness of channel phase deviation and Doppler center. It utilizes an innovative algorithm that combines joint estimation of spatiotemporal coherence with weighted fusion, making it particularly suitable for complex operating modes such as interleaved PRI.

[0041] 3. This invention lays a solid foundation for the system to realize its high-performance imaging potential. It ensures the effectiveness of digital beamforming through high-precision phase compensation, thereby reliably realizing high-resolution wide mapping strip (HRWS) imaging and supporting advanced applications such as moving target detection. Attached Figure Description

[0042] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 Flowchart of an inter-channel phase deviation estimation method applicable to staggered pulse interval azimuth multi-channel SAR; Figure 2 This is a structural diagram of an inter-channel phase deviation estimation system applicable to staggered pulse interval azimuth multi-channel SAR; Figure 3 This is a schematic diagram of a SAR image without inter-channel phase deviation. Figure 4 This is a schematic diagram of SAR imaging results when the phase deviation between channels is 45°. Figure 5 This is a schematic diagram of the imaging result after phase deviation correction. Detailed Implementation

[0043] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0044] Example 1 This embodiment provides a method for estimating the inter-channel phase deviation of multi-channel SAR, including the following steps: Step S1: Input interleaved pulse repetition interval azimuth multi-channel SAR echo data; Step S2: Perform distance compression on the echo data of each channel; Step S3: Calculate the instantaneous correlation coefficient between adjacent channels and the optimal correlation coefficient between channels at adjacent azimuth times; Step S4: Adaptive weighted estimation of Doppler center frequency; Step S5: Invert the phase deviation between channels using the Doppler center frequency; Step S6: Correct the echo or imaging data using phase deviation; Step S7: Output the corrected data.

[0045] Further, in step S1, the input azimuth multi-channel SAR echo data is the raw echo data received from the azimuth multi-channel SAR system, and the number of channels is denoted as... The key feature of its transmit and receive modes is that the pulse repetition interval (PRI) is not a fixed value, but follows a preset, time-varying interleaved pattern.

[0046] Furthermore, the calculation of the instantaneous correlation coefficient between adjacent channels and the optimal correlation coefficient between channels at adjacent azimuth times in step S3 specifically includes: Step S3.1: Estimate the correlation coefficient between channels of adjacent azimuth times; for each azimuth time, estimate the correlation coefficient between adjacent channels:

[0047] in, Indicates location and time The distance to the nth sampling point in the m-th receiving channel after compression, superscript Indicates conjugate. Integers, ranging from 1 to , This represents the total number of channels.

[0048] Step S3.2 Estimate the optimal correlation coefficient between adjacent azimuth time channels. To find the two channels with the shortest distance between their three-dimensional spatial positions at the current pulse time and the next pulse time, estimate the optimal coherence coefficient between adjacent time channels; assuming the azimuth time... No. Each channel and orientation time No. The optimal correlation coefficient for each channel can be estimated by expressing the optimal coherence coefficient between channels at adjacent time points as follows:

[0049] in, Indicates location and time The distance to the nth sampling point in the m-th receiving channel after compression, superscript Indicates conjugate. Indicates location and time The pulse repetition interval with the next azimuth time. and Integers, ranging from 1 to , This represents the total number of channels.

[0050] Furthermore, the azimuth time mentioned in step S3.2 No. Each channel and orientation time No. Each channel is selected to satisfy the shortest spatiotemporal distance, that is:

[0051] in, For the direction and time Time The three-dimensional spatial location of each channel Indicates location and time The pulse repetition interval with the next azimuth time. and Integers, ranging from 1 to , This represents the total number of channels.

[0052] Furthermore, the adaptive weighted estimation of the Doppler center frequency based on the result of step S3, as described in step S4, specifically includes: Step S4.1: Instantaneous Doppler center estimation, that is, calculating the estimated value of the instantaneous Doppler center frequency for each azimuth time; Location and Time Doppler center estimate at time for:

[0053] in, Location and time The corresponding pulse repetition frequency, This represents the optimal coherence coefficient between adjacent time channels. This represents the correlation coefficient between adjacent channels.

[0054] Step S4.2: Weighted fusion of Doppler centers across the entire scene, which involves taking a weighted average of all instantaneous estimates obtained in step S4.1 to obtain the Doppler center frequency estimate for the entire scene:

[0055] in, Location and time Doppler center estimate at time, Location and time Weights of the Doppler center estimate at time,

[0056] in, Location and time The corresponding pulse repetition frequency, This represents the optimal coherence coefficient between adjacent time channels. The correlation coefficient between adjacent channels, subscript Representing the One channel.

[0057] Furthermore, the step S5, which involves using the Doppler center frequency to invert the phase deviation between channels, specifically includes: Step S5.1: Calculate the coherence coefficient of adjacent channels across the entire scene. Average the correlation coefficients of adjacent channels calculated at each time step in Step S3.1 over azimuth time to calculate the coherence coefficient of adjacent channels across the entire scene.

[0058] in, This refers to the location and time. Location and time The estimated correlation coefficient between the m-th and (m+1)-th channels.

[0059] Step S5.2: Calculate the phase deviation between adjacent channels :

[0060] in, Let be the full-scene correlation coefficient between the m-th and m+1-th channels. This is the estimated value of the Doppler center for the entire scene. The spatial spacing between the phase centers of adjacent channel antennas. For satellite speed.

[0061] Step S5.3: Calculate the phase deviation of each channel relative to the reference channel. The phase deviation between the m-th channel and the 1st channel is:

[0062] in, This represents the phase deviation between the k-th channel and the (k+1)-th channel.

[0063] This embodiment belongs to the field of synthetic aperture radar (SAR) signal processing technology, specifically involving a channel error correction method for a multi-channel SAR system, which is particularly suitable for self-correction of channel phase deviation and high-precision imaging of azimuth multi-channel SAR systems using staggered pulse repetition interval (PRI) working mode.

[0064] The present invention also provides an inter-channel phase deviation estimation system for multi-channel SAR. The inter-channel phase deviation estimation system for multi-channel SAR can be implemented by executing the process steps of the inter-channel phase deviation estimation method for multi-channel SAR. That is, those skilled in the art can understand the inter-channel phase deviation estimation method for multi-channel SAR as a preferred embodiment of the inter-channel phase deviation estimation system for multi-channel SAR.

[0065] Example 2 This embodiment provides an inter-channel phase deviation estimation system for multi-channel SAR, including: Module M1: Data input module; Module M2: Distance compression module; Module M3: Correlation coefficient calculation module; Module M4: Doppler estimation module; Module M5: Phase Inversion Module; Module M6: Calibration Output Module.

[0066] Furthermore, the M1 data input module inputs azimuth multi-channel SAR echo data, with the number of channels being... The echo data is transmitted and received using an interlaced pulse repetition interval mode.

[0067] Furthermore, the distance compression module M2 performs distance compression on the echo data of each channel.

[0068] Furthermore, the M3 correlation coefficient calculation module calculates the instantaneous correlation coefficient between adjacent channels and the optimal correlation coefficient between channels at adjacent azimuth times.

[0069] Furthermore, the M4 Doppler estimation module adaptively weights the Doppler center frequency based on the results of the M3 module.

[0070] Furthermore, the M5 phase inversion module utilizes the Doppler center frequency to invert the phase deviation between channels.

[0071] Example 3 Those skilled in the art can understand this embodiment as a more specific description of Embodiment 1.

[0072] This embodiment provides a channel phase deviation correction method suitable for interleaved pulse repetition interval azimuth multi-channel SAR, including: Step S1: Input interleaved pulse repetition interval azimuth multi-channel SAR echo data; Step S2: Perform distance compression on the echo data of each channel; Step S3: Calculate the instantaneous correlation coefficient between adjacent channels and the optimal correlation coefficient between channels at adjacent azimuth times; Step S4: Adaptive weighted estimation of Doppler center frequency; Step S5: Invert the phase deviation between channels using the Doppler center frequency; Step S6: Correct the echo or imaging data using phase deviation; Step S7: Output the corrected data.

[0073] Specifically, step S1, inputting azimuth multi-channel SAR echo data, involves receiving raw echo data from an azimuth multi-channel SAR system, with the number of channels denoted as... The key feature is that the echo data is transmitted and received using an interleaved pulse repetition interval pattern. The time interval between different pulse transmission times is not a fixed value, but follows a preset and time-varying interleaving pattern. Necessary preprocessing can be performed before data input, such as data unpacking, format conversion, and invalid data removal.

[0074] Specifically, step S2 performs range compression on the echo data of each channel. The key feature is that range compression is performed separately on the echo data of each received channel. The purpose is to compress the pulse signal, improve range resolution, and suppress range sidelobes. This can be achieved using conventional matched filtering methods, with the reference function being the conjugate of the transmitted linear frequency modulated (LFM) signal replica. This step provides a signal with a higher signal-to-noise ratio for subsequent correlation coefficient calculations.

[0075] Specifically, step S3, calculating the instantaneous correlation coefficient between adjacent channels and the optimal correlation coefficient between channels at adjacent azimuth times, includes: Step S3.1: Estimate the correlation coefficient between channels at instantaneous adjacent azimuth times; Step S3.2: Estimate the optimal correlation coefficient between channels at adjacent azimuth times.

[0076] Specifically, step S3.1, which estimates the correlation coefficient between adjacent channels for each azimuth time, can be expressed as:

[0077] in, Indicates location and time The distance to the nth sampling point in the m-th receiving channel after compression, superscript Indicates conjugate. Integers, ranging from 1 to , This represents the total number of channels.

[0078] Specifically, step S3.2 estimates the optimal correlation coefficient between adjacent azimuth time channels, assuming the azimuth time... No. Each channel and orientation time No. The optimal correlation coefficient for each channel, and the estimated optimal coherence coefficient between adjacent time channels, can be expressed as:

[0079] in, Indicates location and time The distance to the nth sampling point in the m-th receiving channel after compression, superscript Indicates conjugate. Indicates location and time The pulse repetition interval with the next azimuth time. and Integers, ranging from 1 to , This represents the total number of channels.

[0080] Specifically, the azimuth time No. Each channel and orientation time No. Each channel is selected based on the shortest spatiotemporal distance, i.e.

[0081] in, For the direction and time Time The three-dimensional spatial location of each channel Indicates location and time The pulse repetition interval with the next azimuth time. and Integers, ranging from 1 to , This represents the total number of channels.

[0082] Specifically, step S4, based on the result of step S3, adaptively weights and estimates the Doppler center frequency, including: Step S4.1: Instantaneous Doppler center estimation; Step S4.2: Full-scene Doppler center-weighted fusion.

[0083] Specifically, step S4.1, instantaneous Doppler center estimation, azimuth time... Doppler center estimate at time It can be represented as:

[0084] in, Location and time The corresponding pulse repetition frequency, This represents the optimal coherence coefficient between adjacent time channels. This represents the correlation coefficient between adjacent channels.

[0085] Specifically, step S4.2, full-scene Doppler center-weighted fusion, can be expressed as:

[0086] in, Location and time Doppler center estimate at time, Location and time The weights of the Doppler center estimates at time, where It can be represented as:

[0087] in, Location and time The corresponding pulse repetition frequency, This represents the optimal coherence coefficient between adjacent time channels. The correlation coefficient between adjacent channels, subscript Representing the One channel.

[0088] Specifically, step S5 utilizes the Doppler center frequency to invert the phase deviation between channels, including: Step S5.1: Calculate the coherence coefficients of adjacent channels across the entire scene; Step S5.2: Calculate the phase deviation between adjacent channels; Step S5.3: Calculate the phase deviation of each channel relative to the reference channel.

[0089] Specifically, step S5.1 calculates the coherence coefficients of adjacent channels across the entire scene:

[0090] in, This refers to the location and time. Location and time The estimated correlation coefficient between the m-th and (m+1)-th channels.

[0091] Specifically, step S5.2 calculates the phase deviation between adjacent channels. :

[0092] in, Let be the full-scene correlation coefficient between the m-th and m+1-th channels. This is the estimated value of the Doppler center for the entire scene. The spatial spacing between the phase centers of adjacent channel antennas. For satellite speed.

[0093] Specifically, step S5.3 calculates the phase deviation between the m-th channel and the 1st channel:

[0094] in, This represents the phase deviation between the k-th channel and the (k+1)-th channel.

[0095] Specifically, step S6 corrects the echo or imaging data using phase deviation, adjusting the phase deviation between the m-th channel and the 1st channel estimated in step S5.3. Used to correct data.

[0096] Specifically, step S7 outputs the corrected data, which is the data after phase deviation correction, for subsequent applications such as high-resolution wide-span imaging, moving target detection (GMTI), and interferometry.

[0097] The present invention also provides an inter-channel phase deviation correction system suitable for interleaved pulse interval azimuth multi-channel SAR. The inter-channel phase deviation estimation system suitable for interleaved pulse interval azimuth multi-channel SAR can be implemented by executing the process steps of the inter-channel phase deviation estimation method suitable for interleaved pulse interval azimuth multi-channel SAR. That is, those skilled in the art can understand the inter-channel phase deviation estimation method suitable for interleaved pulse interval azimuth multi-channel SAR as a preferred embodiment of the inter-channel phase deviation estimation system suitable for interleaved pulse interval azimuth multi-channel SAR.

[0098] Example 4 Those skilled in the art can understand this embodiment as a more specific description of Embodiment 2.

[0099] This embodiment provides an inter-channel phase deviation correction system suitable for interleaved pulse repetition interval azimuth multi-channel SAR, including: Module M1: Data input module; Module M2: Distance compression module; Module M3: Correlation coefficient calculation module; Module M4: Doppler estimation module; Module M5: Phase Inversion Module; Module M6: Calibration Output Module.

[0100] Furthermore, the M1 data input module inputs azimuth multi-channel SAR echo data, with the number of channels being... The echo data is transmitted and received using an interlaced pulse repetition interval mode.

[0101] Furthermore, the distance compression module M2 performs distance compression on the echo data of each channel.

[0102] Furthermore, the M3 correlation coefficient calculation module calculates the instantaneous correlation coefficient between adjacent channels and the optimal correlation coefficient between channels at adjacent azimuth times.

[0103] Furthermore, the M4 Doppler estimation module adaptively weights the Doppler center frequency based on the results of the M3 module.

[0104] Furthermore, the M5 phase inversion module utilizes the Doppler center frequency to invert the phase deviation between channels.

[0105] Furthermore, the M6 ​​correction output module corrects the echo or imaging data using phase deviation and outputs the corrected data.

[0106] The invention is illustrated here with simulation experiments. The simulated spaceborne SAR system is a dual-channel system with a channel spacing of 3.11 meters. The system uses a periodic repetitive pulse interval, with a pulse interval of 404.2 within one cycle. 388.5 381.1 and 374.0 SAR images with inter-channel phase deviation, such as Figure 3 As shown. When the phase deviation between channels is 45°, the SAR imaging results are as follows. Figure 4 As can be seen by comparing the two images, a large number of areas of azimuth blurring appeared in the imaging result at this time. The inter-channel phase deviation estimated using the method of this invention is 45.01°. After phase deviation correction, the imaging result is as follows. Figure 5 As shown in the figure, the azimuth blur caused by phase deviation has been effectively suppressed.

[0107] This invention discloses a channel phase deviation correction method and system applicable to interleaved pulse repetition interval azimuth multi-channel SAR, belonging to the field of synthetic aperture radar signal processing technology. The method includes: inputting azimuth multi-channel SAR echo data; performing range compression on the echo data of each channel; calculating the instantaneous correlation coefficient between adjacent channels and the optimal correlation coefficient between channels at adjacent azimuth times; adaptively weighting and estimating the Doppler center frequency; inverting the inter-channel phase deviation using the Doppler center frequency; correcting the echo or imaging data using the phase deviation; and outputting the corrected data. The system includes a data input module, a range compression module, a correlation coefficient calculation module, a Doppler estimation module, a phase inversion module, and a correction output module to implement the above method.

[0108] This invention utilizes only the statistical characteristics of the echo data itself, without the need for an external calibration source, which significantly improves the accuracy and robustness of phase deviation estimation and effectively overcomes the channel mismatch problem in the staggered pulse repetition interval mode, providing a reliable technical foundation for high-resolution wide-span imaging and moving target detection.

[0109] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0110] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for correcting channel phase deviation in multi-channel SAR, characterized in that, Includes the following steps: Step S1: Acquire raw echo data of interleaved pulse repetition interval azimuth multichannel SAR; Step S2: Perform range compression processing on the raw echo data of each channel obtained in step S1 to obtain the range-compressed echo data of each channel; Step S3: Based on the distance-compressed echo data of each channel obtained in Step S2, estimate the correlation coefficient between adjacent channels at instantaneous times and the optimal correlation coefficient between channels at adjacent azimuth times; Step S4: Combining the instantaneous correlation coefficient between adjacent channels obtained in Step S3 and the optimal correlation coefficient between channels at adjacent azimuth times, perform adaptive weighted estimation of the Doppler center frequency; Step S5: Based on the Doppler center frequency estimation results obtained in step S4, the phase deviation values ​​between each channel are obtained by inversion; Step S6: Using the inter-channel phase deviation value obtained from step S5, perform phase correction processing on the range-compressed echo data or the imaging data generated based on the echo data in step S2. Step S7: Output the echo data or imaging data after phase deviation correction in step S6 to complete the entire inter-channel phase deviation estimation and correction process.

2. The channel phase deviation correction method for multi-channel SAR according to claim 1, characterized in that, Step S3 specifically includes the following steps: Step S3.1: Estimate the correlation coefficient between instantaneously adjacent channels. The estimation expression for the correlation coefficient between instantaneously adjacent channels is: in, Indicates location and time The correlation coefficient between the m-th receiving channel and the (m+1)-th receiving channel; Indicates location and time The distance to the sampling point at the nth sampling point of the mth receiving channel after compression; Indicates location and time The distance to the nth sampling point in the (m+1)th receiving channel after compression; superscript Indicates conjugate; Integers, ranging from 1 to , Indicates the total number of channels; This represents the summation of the distance-compressed signals at all distance sampling points in the receiving channel; Step S3.2: Estimate the optimal correlation coefficient between channels at adjacent azimuth times, and define the azimuth time. No. Each channel and orientation time No. If the correlation coefficient of a channel is optimal, then the estimated expression for the optimal correlation coefficient between channels at adjacent azimuth times is: in, Indicates location and time No. Each channel and orientation time No. Correlation coefficients between channels; Indicates location and time First The compressed signal at the nth distance sampling point of each receiving channel; Indicates location and time First The compressed signal at the nth distance sampling point of each receiving channel; superscript Indicates conjugate; Indicates location and time The pulse repetition interval with the next azimuth time; and Integers, ranging from 1 to , This represents the total number of channels.

3. The channel phase deviation correction method for multi-channel SAR according to claim 2, characterized in that, In step S3.2, the azimuth time No. Each channel and orientation time No. The channel selection satisfies the shortest channel spatiotemporal distance, expressed as: in, Indicates the first The first channel and the first The spatiotemporal distance of each channel; argmin|.| is the minimum value function; For the direction and time Time The three-dimensional spatial position of each channel; Indicates the direction and time as Time The three-dimensional spatial position of each channel; Indicates location and time The pulse repetition interval with the next azimuth time; and Integers, ranging from 1 to , This represents the total number of channels.

4. The channel phase deviation correction method for multi-channel SAR according to claim 2, characterized in that, Step S4 specifically includes the following steps: Step S4.1: Estimate the instantaneous Doppler center, azimuth and time. Doppler center estimate at time for: in, Location and time The corresponding pulse repetition frequency, where angle{·} is the argument function. This represents the optimal coherence coefficient between adjacent time channels. The multiplication symbol is used. The correlation coefficient between adjacent channels; Step S4.2: Perform weighted fusion of the Doppler centers across the entire scene, expressed as: in, Location and time Doppler center estimate at time, Indicates time for all directions Sum the corresponding terms. Location and time The weight of the Doppler center estimate at time is calculated using the following formula: in, Location and time The corresponding pulse repetition frequency, This represents the optimal coherence coefficient between adjacent time channels. This represents the correlation coefficient between adjacent channels.

5. The channel phase deviation correction method for multi-channel SAR according to claim 2, characterized in that, Step S5 specifically includes the following steps: Step S5.1: Calculate the coherence coefficient of adjacent channels across the entire scene. The calculation formula is: in, This refers to the location and time. Location and time The estimated correlation coefficient between the m-th and (m+1)-th channels; Step S5.2: Calculate the phase deviation between adjacent channels The calculation formula is: in, Let be the full-scene correlation coefficient between the m-th and m+1-th channels. j Represents the imaginary unit. This is the estimated value of the Doppler center for the entire scene. The spatial spacing between the phase centers of adjacent channel antennas. For satellite speed; Step S5.3: Calculate the phase deviation of each channel relative to the reference channel, specifically the phase deviation between the m-th channel and the 1st channel. for: in, This represents the phase deviation between the k-th channel and the (k+1)-th channel.

6. A channel phase offset correction system for multi-channel SAR, characterized in that, Includes the following modules: Module M1: Acquires raw echo data from interleaved pulse repetition interval azimuth multichannel SAR; Module M2: Performs distance compression processing on the raw echo data of each channel obtained in module M1 to obtain distance-compressed echo data of each channel; Module M3: Based on the distance-compressed echo data of each channel obtained from Module M2, estimate the correlation coefficient between adjacent channels at instantaneous times and the optimal correlation coefficient between channels at adjacent azimuth times; Module M4: Combining the instantaneous correlation coefficient between adjacent channels obtained from Module M3 and the optimal correlation coefficient between channels at adjacent azimuth times, an adaptive weighted estimation of the Doppler center frequency is performed; Module M5: Based on the Doppler center frequency estimation results obtained from Module M4, the phase deviation values ​​between each channel are inverted to obtain the phase deviation values. Module M6: Using the inter-channel phase deviation value obtained by inversion from module M5, perform phase correction processing on the range-compressed echo data in module M2 or the imaging data generated based on the echo data; Module M7: Outputs the phase-biased echo data or imaging data from module M6, completing the entire inter-channel phase bias estimation and correction process.

7. The channel phase deviation correction system for multi-channel SAR according to claim 6, characterized in that, Module M3 specifically includes the following modules: Module M3.1: Estimates the correlation coefficient between instantaneously adjacent channels. The estimation expression for the correlation coefficient between instantaneously adjacent channels is: in, Indicates location and time The correlation coefficient between the m-th receiving channel and the (m+1)-th receiving channel; Indicates location and time The distance to the sampling point at the nth sampling point of the mth receiving channel after compression; Indicates location and time The distance to the nth sampling point in the (m+1)th receiving channel after compression; superscript Indicates conjugate; Integers, ranging from 1 to , Indicates the total number of channels; This represents the summation of the distance-compressed signals at all distance sampling points in the receiving channel; Module M3.2: Estimates the optimal correlation coefficient between channels at adjacent azimuth times, defining azimuth times. No. Each channel and orientation time No. If the correlation coefficient of a channel is optimal, then the estimated expression for the optimal correlation coefficient between channels at adjacent azimuth times is: in, Indicates location and time No. Each channel and orientation time No. Correlation coefficients between channels; Indicates location and time First The compressed signal at the nth distance sampling point of each receiving channel; Indicates location and time First The compressed signal at the nth distance sampling point of each receiving channel; superscript Indicates conjugate; Indicates location and time The pulse repetition interval with the next azimuth time; and Integers, ranging from 1 to , This represents the total number of channels.

8. The channel phase deviation correction system for multi-channel SAR according to claim 7, characterized in that, In module M3.2, the azimuth time No. Each channel and orientation time No. The channel selection satisfies the shortest channel spatiotemporal distance, expressed as: in, Indicates the first The first channel and the first The spatiotemporal distance of each channel; argmin|.| is the minimum value function; For the direction and time Time The three-dimensional spatial position of each channel; Indicates the direction and time as Time The three-dimensional spatial position of each channel; Indicates location and time The pulse repetition interval with the next azimuth time; and Integers, ranging from 1 to , This represents the total number of channels.

9. The channel phase deviation correction system for multi-channel SAR according to claim 7, characterized in that, Module M4 specifically includes the following modules: Module M4.1: Estimates the instantaneous Doppler center, azimuth-time. Doppler center estimate at time for: in, Location and time The corresponding pulse repetition frequency, where angle{·} is the argument function. This represents the optimal coherence coefficient between adjacent time channels. The multiplication symbol is used. The correlation coefficient between adjacent channels; Module M4.2: Performs weighted fusion of Doppler centers across the entire scene; the expression is: in, Location and time Doppler center estimate at time, Indicates time for all directions Sum the corresponding terms. Location and time The weight of the Doppler center estimate at time is calculated using the following formula: in, Location and time The corresponding pulse repetition frequency, This represents the optimal coherence coefficient between adjacent time channels. This represents the correlation coefficient between adjacent channels.

10. The channel phase deviation correction system for multi-channel SAR according to claim 7, characterized in that, Module M5 specifically includes the following modules: Module M5.1: Calculates the coherence coefficient of adjacent channels across the entire scene. The calculation formula is: in, This refers to the location and time. Location and time The estimated correlation coefficient between the m-th and (m+1)-th channels; Module M5.2: Calculates the phase deviation between adjacent channels The calculation formula is: in, Let be the full-scene correlation coefficient between the m-th and m+1-th channels. j Represents the imaginary unit. This is the estimated value of the Doppler center for the entire scene. The spatial spacing between the phase centers of adjacent channel antennas. For satellite speed; Module M5.3: Calculates the phase deviation of each channel relative to the reference channel, and the phase deviation between the m-th channel and the 1st channel. for: in, This represents the phase deviation between the k-th channel and the (k+1)-th channel.

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