Abstract
Synthetic Aperture Radar has been an emerging technology to cope with the huge amount of data to cover a wide swath and high-resolution. The data collected consists of both range and cross-range samples. Frequency Modulated Continuous Wave(FMCW) radar generates pulses with continuous PRI(Pulse Repetition Interval). To cope with the huge amount of data it is necessary to compress it before transmission to downlink. The quantization of data is done to reduce the bit/sample of data. In the frequency domain, efficient compression can be done using transform methods. To compress the data various techniques have been established. Block Adaptive Quantization combined with various transforms gives efficient compression compared to only BAQ. This paper covers the Wavelet Transform method compression of raw real SAR data. Block Adaptive Quantization of data is done along with DWT. The results have been evaluated with the Traditional BAQ algorithm. Improved Signal to Noise ratio has been obtained using wavelet BAQ.
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