STAP techniques for real-time processing in heterogeneous clutter

Abstract:
The use of conventional STAP (space-time adaptive processing) for detection of moving targets in ground clutter is limited mainly by two properties: firstly the computational workload required for adaptation and filtering, secondly by imperfect adaptation based on secondary clutter data obtained from heterogeneous environments. There are basically two kinds of processing architectures which promise to overcome these problems: 1. dimension reducing transforms (DRT), 2. direct data domain (3D) processing. In this paper, the option of combining dimension reducing transforms with direct data domain processing is analysed in terms of performance and computational workload.