This thesis is concerned with the design and implementation of a Synthetic Aperture Radar (SAR) data processor. The implementation of the processing is based on a standard sequential approach to the problem and employs commonly used algorithms. The processing was done using the C language running on an IBM Compatible Personal Computer. The raw data processed was that obtained from the Shuttle Imaging Radar B (SIRB) and was supplied by the Jet Propulsion Laboratories (JPL) in California. The basic functions performed by the software include range and azimuth processing, which involve the match filtering of reference functions with the raw data. Compensation for the effects of being a spaceborne SAR were also implemented, which involved compensation for the effect of planet rotation and radar height. Images processed by JPL of the same area were also available, which allowed for direct comparisons between the outputs of the two SAR processors. The images produced were passed through a number of filters, to improve the image quality, and resulted in favourable comparisons to the JPL generated images. The actual images are included in the later sections of the thesis.

International Telemetering Conference Proceedings / October 26-29, 1998 / Town & Country Resort Hotel and Convention Center, San Diego, California / This paper discusses the evolution of the ground satellite communication systems and the efforts made by the Goddard Space Flight Center's (GSFC) Advanced Architectures and Automation (AAA) branch, Code 588 to bring satellite scientific data to the user’s desktop. Primarily, it describes the next generation desktop system, its architecture and processing capabilities, which provide autonomous high-performance telemetry acquisition at the lowest possible cost. It also discusses the planning processes and the applicability of new technologies for communication needs in the next century. The paper is presented in terms simple for those not very familiar with current space programs to understand.

The advanced signal processing systems of today require extreme data throughput and low power consumption.The only way to accomplish this is to use parallel processor architecture with efficient algorithms.The aim of this thesis was to evaluate the use of parallel processor architecture in Radar signal processingapplications where the processor has to compute complex calculations. This has been done by implementingdemanding algorithms on Ambric Am2000 family Massively Parallel Processor Array (MPPA). The Ambricplatform evaluated in terms of Latency, Cycle Count per output sample and Efficiency of the developmenttools.The two algorithms chosen for implementation are Fast Fourier Transform (FFT) and Finite Impulse Response(FIR) algorithms. We have implemented parameterized versions of FFT and FIR. The FFT algorithmimplemented for N-point input for the range of 8 point to 32 point for complex input variables. It works for anygiven number of inputs within the range for given parameter values and mapped on Ambric processor withfixed point radix - 2. Another one is FIR algorithm for the range of 12 Taps to 64 Taps for complex inputvariables. The Implementation of algorithms shows that high level of parallelism can be achieved in MassivelyParallel Processing Arrays (MPPA) especially on complex algorithms like FFT and FIR.