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A Novel Chirp-Z Transform Algorithm for Multi-Receiver Synthetic Aperture Sonar Based on Range Frequency Division
A Novel Chirp-Z Transform Algorithm for Multi-Receiver Synthetic Aperture Sonar Based on Range Frequency Division
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A Novel Chirp-Z Transform Algorithm for Multi-Receiver Synthetic Aperture Sonar Based on Range Frequency Division
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A Novel Chirp-Z Transform Algorithm for Multi-Receiver Synthetic Aperture Sonar Based on Range Frequency Division
A Novel Chirp-Z Transform Algorithm for Multi-Receiver Synthetic Aperture Sonar Based on Range Frequency Division

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A Novel Chirp-Z Transform Algorithm for Multi-Receiver Synthetic Aperture Sonar Based on Range Frequency Division
A Novel Chirp-Z Transform Algorithm for Multi-Receiver Synthetic Aperture Sonar Based on Range Frequency Division
Journal Article

A Novel Chirp-Z Transform Algorithm for Multi-Receiver Synthetic Aperture Sonar Based on Range Frequency Division

2024
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Overview
When a synthetic aperture sonar (SAS) system operates under low-frequency broadband conditions, the azimuth range coupling of the point target reference spectrum (PTRS) is severe, and the high-resolution imaging range is limited. To solve the above issue, we first convert multi-receivers’ signal into the equivalent monostatic signal and then divide the equivalent monostatic signal into range subblocks and the range frequency subbands within each range subblock in order. The azimuth range coupling terms are converted into linear terms based on piece-wise linear approximation (PLA), and the phase error of the PTRS within each subband is less than π/4. Then, we use the chirp-z transform (CZT) to correct range cell migration (RCM) to obtain low-resolution results for different subbands. After RCM correction, the subbands’ signals are coherently summed in the range frequency domain to obtain a high-resolution image. Finally, different subblocks are concatenated in the range time domain to obtain the final result of the whole swath. The processing of different subblocks and different subbands can be implemented in parallel. Computer simulation experiments and field data have verified the superiority of the proposed method over existing methods.