Abstract
In this letter, a novel method for onboard data reduction for multichannel synthetic aperture radar (SAR) (MC-SAR) systems is presented. Such systems allow for high-resolution imaging of a wide swath but, on the other hand, require for their operation the acquisition and downlink of a huge amount of data: together with the intrinsic requirement related to resolution and swath width, this is due to the use of a pulse repetition frequency (PRF) typically higher than the processed Doppler bandwidth (PBW), which introduces a certain oversampling in the azimuth raw data. In this context, we propose a convenient data reduction strategy, named multichannel block-adaptive quantization (MC-BAQ), which exploits the existing correlation between subsequent azimuth samples by performing a discrete Fourier transform (DFT) of the MC-SAR data block. Then, a variable-bit quantization is applied which allows for the optimization of the resulting performance and data rate. Simulations have been carried out on scenes with distributed scatterers showing different backscatter characteristics to demonstrate that the proposed MC-BAQ allows for a significant reduction of the data volume to be downlinked to the ground at the cost of a modest increase of onboard computational effort.
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