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With recent advances in polarimetry, Synthetic Aperture Radar (SAR) with Hybrid–polarity architecture, a demonstration of compact polarimetry enabled larger swath coverage, reduced PRF and SAR system complexity as compared to fully polarimetric systems. The first Hybrid Polarimetric Space-borne SAR in Earth Observation orbit, India’s Radar Imaging Satellite (RISAT-1) is a new-fangled gateway to remote sensing user community for land and oceanic applications. In response to a right-circular polarized transmitted signal, based on the derived stokes vectors, Stokes parameters are estimated to produce several useful quantitative measures for generating polarimetric decomposed image. m-delta, m-chi and m-alpha polarimetric decomposition methods along with suitable weighting functions in terms of three principal components are implemented which maps Stokes parameters to RGB image space for representing odd bounce, even bounce and volume scattering targets. Various RISAT-1 Hybrid Fine Resolution Stripmap Single-Look Complex SAR datasets acquired over deployed corner reflectors at calibration site, Shadnagar have been considered over which different hybrid polarimetric decomposition techniques are implemented using in-house developed software. Further analysis produced encouraging results with standard point targets like dihedral and trihedral corner reflectors against distributed targets in the same scene to demonstrate the scattering mechanisms as per their characteristics when interacted with a polarized signal were presented in this paper.

Traditional processing of Circular Polarimetric (Compact Polarimetric)—Synthetic Aperture Radar (CP-SAR) images from the Satellites has been done after receiving the raw data in the Ground Station. The availability of million gate FPGAs has given scope for doing many processing steps on-board itself which has given scope for Smart Small Satellites. The feasibility exists especially for small scenes of interest which have limited data in smaller volumes for ease of processing. National Remote Sensing Centre, Indian Space Research Organisation (NRSC, ISRO) have carried out ground processing with software tools hosted in high performance computers, using the m-delta (δ) decomposition method on the L1-SLC data of CP-SAR payload of RISAT-1 satellite for classification. In our research work, the same data set, and m-delta(ẟ) decomposition method have been chosen for implementation and processing in FPGA fabric, for comparison with earlier Ground based processed results. As part of prototyping, an Intel FPGA evaluation board kit was used. Preliminary results are encouraging and can lead to potential future Smart Small Satellite missions with CP-SAR and on-board processing for direct classification of the scene under imaging for its possible direct delivery to the end user. Major advantage of this approach is the reduction in bandwidth, as the volume of data to be downlinked is reduced, due to lower latency, computational and round-trip times, potential scope for delivery to user with near real-time processing.