CELP-like compression of spotlight-mode SAR raw data in transform domain

Transmission of synthetic aperture radar (SAR) data requires large bandwidth due to its inherently high data rate. Consequently, compression of the data is often required. In this paper, we propose a raw SAR data compression algorithm that employs a predictive coding scheme, based on the analysis-by-synthesis encoding method. The proposed algorithm is inspired by code excited linear prediction (CELP) algorithm used in speech compression and exploits the signal correlation across azimuth of the range-wise inverse Fourier transform of the raw SAR data. Our results show that the proposed CELP-like compression algorithm is 6 dB superior to block adaptive quantization (BAQ) in signal-to-noise ratio. Also, we show that the formed SAR image after compression preserves the main features of the captured scene at low data rate contrary to that of BAQ-compressed data.