Knowledge-aided multichannel adaptive SAR/GMTI processing: algorithm and experimental results

Authors:
Di Wu;Daiyin Zhu;Zhaoda Zhu
Affiliations:
College of Information Science and Technology, Nanjing University of Aeronautics & Astronautics, Nanjing, China;College of Information Science and Technology, Nanjing University of Aeronautics & Astronautics, Nanjing, China;College of Information Science and Technology, Nanjing University of Aeronautics & Astronautics, Nanjing, China
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on advances in multidimensional synthetic aperture radar signal processing
Year:
2010

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Abstract

The multichannel synthetic aperture radar ground moving target indication (SAR/GMTI) technique is a simplified implementation of space-time adaptive processing (STAP), which has been proved to be feasible in the past decades. However, its detection performance will be degraded in heterogeneous environments due to the rapidly varying clutter characteristics. Knowledge-aided (KA) STAP provides an effective way to deal with the nonstationary problem in real-world clutter environment. Based on the KA STAP methods, this paper proposes a KA algorithm for adaptive SAR/GMTI processing in heterogeneous environments. It reduces sample support by its fast convergence properties and shows robust to non-stationary clutter distribution relative to the traditional adaptive SAR/GMTI scheme. Experimental clutter suppression results are employed to verify the virtue of this algorithm.