Comparative Analysis between SAR Pulse Compression Techniques

Remote sensing is the backbone for several civilian and military applications. Synthetic Aperture Radar (SAR) is considered as one of the most important tools, which has a significant rule in remote sensing applications. For SAR signal processing, pulse compression techniques aim to obtain a fine map resolution, decrease the peak-transmitted power, and increase Signal to Noise Ratio (SNR) of the sensed target. In this paper, we introduce a performance assessment for two well-known Linear Frequency Modulation (LFM) pulse compression techniques, which are Matching Filtering and Stretch Processing. For matching filtering, it is known as Correlation processing technique. It is mainly used for narrow band and some medium band radar operations. While, stretch processing technique is usually used for high bandwidth LFM signal processing. Besides that, we discuss the properties of the LFM signal and the two compression techniques in both time and frequency domain. Also, the paper investigates the concept of the principle of stationary phase (POSP) and its use in deriving the frequency characteristics for the LFM signal and matched filter output. A mathematical model for each compression technique has been derived such that these models will be used for hardware implementation purpose. For simulation and performance assessment, the two techniques have been analyzed based on some quantitative indices like, Pulse Compression Ratio (PCR) and Peak Side-Lobe Ratio (PSLR).