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Radar HRRP statistical recognition with temporal factor analysis by automatic Bayesian Ying-Yang harmony learning

  • Research Article
  • Published:
Frontiers of Electrical and Electronic Engineering in China

Abstract

Radar high-resolution range profiles (HRRPs) are typical high-dimensional and interdimension dependently distributed data, the statistical modeling of which is a challenging task for HRRP-based target recognition. Supposing that HRRP samples are independent and jointly Gaussian distributed, a recent work [Du L, Liu H W, Bao Z. IEEE Transactions on Signal Processing, 2008, 56(5): 1931–1944] applied factor analysis (FA) to model HRRP data with a two-phase approach for model selection, which achieved satisfactory recognition performance. The theoretical analysis and experimental results reveal that there exists high temporal correlation among adjacent HRRPs. This paper is thus motivated to model the spatial and temporal structure of HRRP data simultaneously by employing temporal factor analysis (TFA) model. For a limited size of high-dimensional HRRP data, the two-phase approach for parameter learning and model selection suffers from intensive computation burden and deteriorated evaluation. To tackle these problems, this work adopts the Bayesian Ying-Yang (BYY) harmony learning that has automatic model selection ability during parameter learning. Experimental results show stepwise improved recognition and rejection performances from the two-phase learning based FA, to the two-phase learning based TFA and to the BYY harmony learning based TFA with automatic model selection. In addition, adding many extra free parameters to the classic FA model and thus becoming even worse in identifiability, the model of a general linear dynamical system is even inferior to the classic FA model.

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Author information

Authors and Affiliations

  1. National Laboratory of Radar Signal Processing, Xidian University, Xi’an, 710071, China

    Penghui Wang, Lan Du, Hongwei Liu & Zheng Bao

  2. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China

    Lei Shi & Lei Xu

Authors
  1. Penghui Wang
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  2. Lei Shi
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  3. Lan Du
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  4. Hongwei Liu
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  5. Lei Xu
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  6. Zheng Bao
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Corresponding author

Correspondence to Lei Xu.

Additional information

Penghui WANG received the B.Eng. degree in communication engineering from the National University of Defense Technology, Changsha, China, in 2005. He is currently working toward the Ph.D degree with the National Laboratory of Radar Signal Processing, Xidian University. His research interests include radar signal processing, radar automatic target recognition (RATR), and pattern recognition.

Lei SHI received the B.Eng. degree in computer science and technology from the University of Science and Technology of China, Hefei, in 2005. He is currently a Ph.D student with the Department of Computer Science and Engineering, the Chinese University of Hong Kong. His research interests include statistical learning and neural computing.

Lan DU received the B.S., M.S. and Ph.D degrees in electronic engineering from Xidian University, Xi’an, China, in Jul. 2001, Mar. 2004 and Jun. 2007 respectively. Her doctoral dissertation was granted Top 100 Doctoral Dissertation in China in 2009. She is currently an Associate Professor in Xidian University. Her main research interests are in the fields of statistical signal processing and machine learning with application to radar target recognition.

Hongwei LIU received the B.Eng. degree from Dalian University of Technology in electronic engineering in 1992, and the M.Eng. and Ph.D degrees in electronic engineering from Xidian University, Xi’an, China, in 1995 and 1999, respectively. He is currently the Director and a Professor with the National Laboratory of Radar Signal Processing, Xidian University. His research interests include radar automatic target recognition (RATR), radar signal processing, and adaptive signal processing.

Lei XU, IEEE Fellow (2001–) and Fellow of International Association for Pattern Recognition (2002–), and Academician of European Academy of Sciences (2002–); a Chair Professor with the Chinese University of Hong Kong, a Chang Jiang Chair Professor with Peking University, China, and an Honorary Professor with Xidian University (See Front. Electr. Electron. Eng. China, 2011, 6(1): 119 for a detailed introduction).

Zheng BAO received the B.Eng. degree from the Communication Engineering Institution of China in 1953. Currently, he is a Professor at Xidian University, Xi’an, China. He is the author or coauthor of six books and has published more than 300 papers. His current research work focuses on the areas of space-time adaptive processing (STAP), radar imaging (SAR/ISAR), radar automatic target recognition (RATR), over-the-horizon radar (OTHR) signal processing, and passive coherent location (PCL). Prof. Bao is a member of the Chinese Academy of Sciences.

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Wang, P., Shi, L., Du, L. et al. Radar HRRP statistical recognition with temporal factor analysis by automatic Bayesian Ying-Yang harmony learning. Front. Electr. Electron. Eng. China 6, 300–317 (2011). https://doi.org/10.1007/s11460-011-0149-8

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  • DOI: https://doi.org/10.1007/s11460-011-0149-8

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