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Multi-aspect SAR Feature Extraction via Gapped-data Amplitude and Phase Estimation |
Fan Hai-yan Zhou Han-fei Li Yu |
School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China |
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Abstract It is valuable to extract multi-aspect SAR feature for radar object recognition. The Gapped-data Amplitude and Phase EStimation (GAPES) are modified to extract multi-aspect SAR feature. Multi-aspect SAR Feature Extraction is a parameter estimation issue with gapped-data case. This algorithm does not need the parametric model of object. In addition, there is no need to fulfill the gapped data and it avoids the error induced by the interpolation. The new approach is not only able to improve the estimative precision of location and amplitude, but also to improve the resolution. Numerical experiments are provided to demonstrate the performance of the algorithm and to show the advantages of multi-aspect SAR data to reconstruct object.
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Received: 02 May 2012
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Corresponding Authors:
Fan Hai-yan
E-mail: hy_fan@yeah.net
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