Adaptive processing for airborne surveillance radar

Future airborne surveillance radars will be required to detect and locate targets in the presence of intense ground clutter and interference. This paper presents an overview of the radar problem and the classes of adaptive algorithm architectures that may be employed. We describe the characteristics of the target and interference signals in the spatial and temporal dimensions observed by a pulse-Doppler radar. A combination of spatial and space-time adaptive processing (STAP) techniques are required to mitigate the variety of interference sources to be expected. Computational complexity and estimation of the interference force consideration of partially adaptive, or reduced-dimension adaptive architectures. A combination of fixed preprocessor filtering and judicious choice of training strategies, can result in substantial dimensionality reduction while maintaining near-optimum performance.