Radar Data Compression and Matched Filtering using Digital Signal Processing Techniques

Abstract

Synthetic Aperture Radar is an imaging radar, used to generate microwave images of earth surface. SAR produces very huge amount of data, which is In Phase Modulated (I) and Quadrature Phase Modulated (Q) signals, treated as raw data.Raw Data can further be processed for Compression which is known as Range Compression. Because of limited on board storage and data rates, it is desired to compress the SAR data.For that Block Adaptive Quantization (BAQ suits SAR data the most. It consists of adapting the step size of a quantizer based on mean and variance of the input and then quantize each sample to Matched Filtering and Demramping. In matched filtering two the respected level of quantization. The another method is Block complex FFT operations, one complex multiplication and one Histogram Equalization Quantization (BHEQ) in which samples complex IFFT is required whereas in deramping method, only are normalized to variance and same quantizer is used. In this one complex multiplication and a single complex FFT is paper matlab simulation results of Range Compression by required. matched filtering and deramping method, BAQ/BHEQ on Raw data are shown. Further comparison is done between standard Currently the best scheme for SAR data compression is and achieved values of Mean Square Error (MSE) and Signal to Noise Ratio(SNR).