Application of fast projection techniques without eigenanalysis to STAP

In ground surveillance from an airborne or space-based radar it is desirable to be able to detect small and slowly moving targets, within severe ground clutter. For operational moving target indication (MTI) systems the clutter filter coefficients have to be updated frequently due to rapidly changin...

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Bibliographic Details
Main Authors: Gierull, C.H., Balaji, B.
Format: Conference Proceeding
Language:English
Subjects:
Airborne radar
Applied sciences
Detection, estimation, filtering, equalization, prediction
Detectors
Exact sciences and technology
Filters
Information, signal and communications theory
Interference
Jamming
Phased arrays
Radar clutter
Radar detection
Radiolocalization and radionavigation
Signal and communications theory
Signal, noise
Spaceborne radar
Surveillance
Telecommunications
Telecommunications and information theory
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Summary:In ground surveillance from an airborne or space-based radar it is desirable to be able to detect small and slowly moving targets, within severe ground clutter. For operational moving target indication (MTI) systems the clutter filter coefficients have to be updated frequently due to rapidly changing interference environment. This paper examines the small sample size performance of different fast fully adaptive space-time processors (STAP) and compares it to the optimum-detector performance. These previously proposed techniques, named matrix transformation based projection (MTP) and lean matrix inversion (LMI), were originally developed to provide fast jammer suppression in phased array radars with many elements. For this application they have been proven to operate with near-optimum performance, yet with a computational expense extremely reduced from that of the optimum detector in most practical cases. The investigation herein focuses on the performance achieved when only a very few data samples are available to adapt (update) the clutter filter coefficient.
DOI:10.1109/NRC.2002.999748