Predictive-transform space-time processing for airborne MTI radar

Abstract

A comprehensive predictive-transform (PT) space-time antenna array processor is presented which optimally integrates two distinct sensor array processing strategies, viz.,optimum multichannel sidelobe cancellation (prediction) and optimum beamforming (transformation). The crux of the technique is the utilization of a multichannel whitening model obtained from a previously developed PT signal modeling procedure. As with previous PT applications, such as in coding and estimation, the synergistic effect of the prediction and transformation mechanisms provide additional means for reducing both design and implementation complexity while gradually trading off performance-as measured by the degree of clutter cancellation for the application considered herein. The comprehensive nature of the PT approach is revealed by recognizing that it subsumes, as special cases, such processing strategies as the optimal sidelobe canceller (pure prediction), optimal beamformer (pure transformation), and other techniques. A new space-time processing architecture is presented which yields substantially better clutter cancellation performance, for the airborne MTI radar problem, over existing hybrid processing strategies, such as single channel optimal MTI followed by optimum beamforming, with only a modest increase in complexity. >