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Coding-Based Data Compression for Multichannel SAR
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DOI：10.1109/LGRS.2024.3510433.png)
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Abstract
En 中文
Multichannel synthetic aperture radar (MC-SAR) allows for high-resolution imaging of a wide swath (HRWS), at the cost of acquiring and downlinking a significantly larger amount of data, compared with conventional SAR systems. In this letter, we discuss the potential of efficient data volume reduction (DVR) for MC-SAR. Specifically, we focus on methods based on transform coding (TC) and linear predictive coding (LPC), which exploit the redundancy introduced in the raw data by the finer azimuth sampling peculiar to the MC system. The proposed approaches, in combination with a variable-bit quantization, allow for the optimization of the resulting performance and data rate. We consider three exemplary yet realistic MC-SAR systems, and we conduct simulations and analyses on synthetic SAR data considering different radar backscatter distributions, which demonstrate the effectiveness of the proposed methods.
Keywords:
Azimuth
Synthetic aperture radar
Doppler effect
Quantization (signal)
Backscatter
Encoding
Autocorrelation
Transform coding
Redundancy
Linear predictive coding
Data volume reduction (DVR)
multichannel (MC) synthetic aperture radar (SAR)
raw data quantization
SAR
Journal
IF:
16.4
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1.0W
Citations:
5.1K