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Journal of Electrical and Computer Engineering
Volume 2015, Article ID 478971, 10 pages
Research Article

Time-Frequency Feature Extraction of HRRP Using AGR and NMF for SAR ATR

1College of Communication Engineering, Chongqing University, Chongqing 400044, China
2Department of Communication Commanding, Chongqing Communication Institute, Chongqing 400035, China

Received 12 December 2014; Revised 4 May 2015; Accepted 25 May 2015

Academic Editor: Sven Nordholm

Copyright © 2015 Xinzheng Zhang et al. 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.


A new approach to classify synthetic aperture radar (SAR) targets based on high range resolution profiles (HRRPs) is presented. Features from each of the target HRRPs are extracted via the nonnegative matrix factorization (NMF) algorithm in time-frequency domain represented by adaptive Gaussian representation (AGR). Firstly, SAR target images have been converted into HRRPs. And the time-frequency matrix for each of HRRPs is obtained by using AGR. Secondly, the time-frequency feature vectors are extracted from the time-frequency matrix utilizing NMF. Finally, hidden Markov models (HMMs) are employed to characterize the time-frequency feature vectors corresponding to one target and are used to being the recognizer. To demonstrate the performance of the proposed approach, experiments are performed in the 10-target MSTAR public dataset. The results support the effectiveness of the proposed technique for SAR automatic target recognition (ATR).