| A challenging problem faced by Ground Moving Target Indicator (GMTI) radars on both airborne and spaceborne platforms is the ability to detect slow moving targets due the presence of non-stationary and heterogeneous ground clutter returns. Space-Time Adaptive Processing techniques process both the spatial signals from an antenna array as well as radar pulses simultaneously to aid in mitigating this clutter which has an inherent Doppler shift due to radar platform motion, as well as spreading across Angle-Doppler space attributable to a variety of factors.;Additional problems such as clutter aliasing, widening of the clutter notch, and range dependency add additional complexity when the radar is bistatic in nature, and vary significantly as the bistatic radar geometry changes with respect to the targeted location. The most difficult situation is that of a spaceborne radar system due to its high velocity and altitude with respect to the earth. A spaceborne system does however offer several advantages over an airborne system, such as the ability to cover wide areas and to provide access to areas denied to airborne platforms.;This dissertation examines both monostatic and bistatic radar performance based upon a computer simulation developed by the author, and explores the use of both optimal STAP and reduced dimension STAP architectures to mitigate the modeled clutter returns. Factors such as broadband jamming, wind, and earth rotation are considered, along with their impact on the interference covariance matrix, constructed from sample training data. Calculation of the covariance matrix in near real time based upon extracted training data is computer processor intensive and reduced dimension STAP architectures relieve some of the computation burden. The problems resulting from extending both monostatic and bistatic radar systems to space are also simulated and studied. |
