A STAP Approach for Bistatic Space-Based GMTI Radar

In this paper, we describe a space-time adaptive processing (STAP) approach for bistatic space-based radar (SBR) ground moving target indication (GMTI) systems. A candidate bistatic SBR GMTI system employing a transmitter at medium earth orbit (MEO) and an airborne receiver is defined. To provide enhanced estimation of the clutter statistics, we apply a knowledge-aided STAP approach based on an efficient form of the expectation-maximization (EM) algorithm for estimating covariance matrices in non-stationary interference. Knowledge-aided processing using multiple CPI data-cubes is performed to build an earthreferenced clutter reflectivity data-base. Model covariance matrices derived from the reflectivity database are inputs to the EM procedure, which estimates a residual covariance matrix. Performance is compared to that of standard STAP processing and higher order Doppler warping in a simulated 90° bistatic angle SBR scenario with terrain height variations determined from digital terrain elevation data (DTED).