Multiresolution Signal Processing Techniques for Ground Moving Target Detection Using Airborne Radar
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Multiresolution Signal Processing Techniques for Ground Moving Target Detection Using Airborne Radar Jameson S. Bergin and Paul M. Techau Information Systems Laboratories, Inc., 8130 Boone Boulevard, Suite 500, Vienna, VA 22182, USA Received 1 November 2004; Revised 15 April 2005; Accepted 25 April 2005 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. Copyright © 2006 J. S. Bergin and P. M. Techau. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
A major goal of the Defense Advanced Research Projects Agency’s Knowledge-Aided Sensor Signal Processing and Expert Reasoning (KASSPER) program [1–4] is to develop new techniques for detecting and tracking slow-moving surface targets that exhibit maneuvers such as stops and starts. Therefore, it is logical to assume that a combination of SAR and GMTI processing may offer a solution to the problem. 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. 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 fast-moving (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.
For exampl
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