Theory and application of covariance matrix tapers for robustadaptive beamforming
IEEE Transactions on Signal Processing
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Synthetic aperture radar (SAR) exploits very high spatial resolution via temporal integration and ownship motion to reduce the background clutter power in a given resolution cell to allow detection of nonmoving targets. Ground moving target indicator (GMTI) radar, on the other hand, employs much lower-resolution processing but exploits relative differences in the space-time response between moving targets and clutter for detection. Therefore, SAR and GMTI represent two different temporal processing resolution scales which have typically been optimized and demonstrated independently to work well for detecting either stationary (in the case of SAR) or exo-clutter (in the case of GMTI) targets. Based on this multiresolution interpretation of airborne radar data processing, there appears to be an opportunity to develop detection techniques that attempt to optimize the signal processing resolution scale (e.g., length of temporal integration) to match the dynamics of a target of interest. This paper investigates signal processing techniques that exploit long CPIs to improve the detection performance of very slow-moving targets.