Application of the Global Matched Filter to Stap Data an Efficient Algorithmic Approach

The global matched filter (GMF) is a mean to solve simultaneously detection and estimation problems. It has been applied mainly in source localization and delay estimation problems where the amount of data to be handled is reasonably small. This is not the case in the space time adaptive processing (STAP) context where the amount of data is extremely large and constitutes probably the major challenge. We present a very efficient algorithm that allows to apply the GMF to problems having several thousands unknowns. This allows its application to the STAP data. We detail both the algorithm and the implementation of the GMF to the STAP data. Since the GMF is a high resolution technique it outperforms the algorithms that are traditionally used in this context