Eigen-Template-Based HRR-ATR with Multi-Look and Time-Recursion

Automatic target recognition (ATR) using high range resolution (HRR) radar signatures is developed using classical Bayesian multiple hypothesis theory. An eigen-template-based matched filtering (ETMF) algorithm is presented where the templates are formed using the dominant range-space eigenvector of detected HRR training profiles and classification is performed using normalized matched filtering (MF). The proposed approach is extended to multi-look and sequential ATR where new observation profiles are recursively combined probabilistically with previous steps to update ATR results, which is useful for simultaneous recognition and tracking of moving targets. An HRR-specific profile normalization scheme is presented to satisfy matched filter requirements. Classification performance of the proposed method has been compared with a linear least-squares method and hidden Markov model (HMM) approach using MSTAR data collection.

[1]  Bahram Javidi,et al.  Physics of Automatic Target Recognition , 2007 .

[2]  Jim Schroeder,et al.  Automated Target Recognition Using the Karhunen-Loéve Transform with Invariance , 2002, Digit. Signal Process..

[3]  Nan Chen,et al.  Target Recognition Based on the Self-Correlation Function of HRRP , 2010, 2010 International Conference on Electrical and Control Engineering.

[4]  Louis L. Scharf,et al.  Matched subspace detectors , 1994, IEEE Trans. Signal Process..

[5]  Bart Kahler,et al.  An ATR challenge problem using HRR data , 2008, SPIE Defense + Commercial Sensing.

[6]  Eric Kostlan.  Statistical complexity of dominant eigenvector calculation , 1991, J. Complex..

[7]  Gerald Fortney.  A private conversation , 1997 .

[8]  Seung-Ku Han,et al.  EFFICIENT RADAR TARGET RECOGNITION USING A COMBINATION OF RANGE PROFILE AND TIME- FREQUENCY ANALYSIS , 2010 .

[9]  Renbiao Wu,et al.  ATR scheme based on 1-D HRR profiles , 2002 .

[10]  Arnab K. Shaw,et al.  Automatic target recognition using Eigen templates , 1998, Defense, Security, and Sensing.

[11]  Joseph A. O'Sullivan,et al.  Automatic target recognition using sequences of high resolution radar range-profiles , 2000, IEEE Trans. Aerosp. Electron. Syst..

[12]  Alessio Balleri,et al.  Analysis of acoustic echoes from a bat-pollinated plant species: insight into strategies for radar and sonar target classification , 2012 .

[13]  Robert L. Williams,et al.  Automatic target recognition of time critical moving targets using 1D high range resolution (HRR) radar , 1999 .

[14]  Erik Blasch,et al.  Robust multi-look HRR ATR investigation through decision-level fusion evaluation , 2008, 2008 11th International Conference on Information Fusion.

[15]  Erik Blasch,et al.  Impact of HRR radar processing on moving target identification performance , 2009, 2009 12th International Conference on Information Fusion.

[16]  G. J. Owirka,et al.  Automatic target recognition using enhanced resolution SAR data , 1999 .

[17]  Raj Bhatnagar,et al.  A hybrid system for target classification , 1997, Pattern Recognit. Lett..

[18]  Lawrence Carin,et al.  Identification of ground targets from sequential high-range-resolution radar signatures , 2002 .

[19]  Roland Jonsson,et al.  Comparison of some HRR-classification algorithms , 2001, SPIE Defense + Commercial Sensing.

[20]  Alessio Balleri,et al.  Classification of flowers by bats: comparison with the radar case , 2009, 2009 International Waveform Diversity and Design Conference.

[21]  Hans Driessen,et al.  2D spatial model matching using HRR multi-radar data , 2008, 2008 11th International Conference on Information Fusion.

[22]  Lee C. Potter,et al.  Model-based classification of radar images , 2000, IEEE Trans. Inf. Theory.

[23]  J. H. Wilkinson.  The algebraic eigenvalue problem , 1966 .

[24]  Lang Hong,et al.  A distributed multirate IMM algorithm for multiplatform tracking , 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

[25]  Krishna M. Pasala,et al.  HRR Radar Signature Database Validation for ATR: An Information Theoretic Approach , 2011, IEEE Transactions on Aerospace and Electronic Systems.

[26]  Arnab K. Shaw,et al.  Robust HRR radar target identification by hybridization of HMM and eigen-template-based matched filtering , 2003, SPIE Defense + Commercial Sensing.

[27]  S. C. Gustafson,et al.  Wavelet preprocessing for high range resolution radar classification , 2001 .

[28]  Richard Alan Mitchell.  Robust high range resolution radar target identification using a statistical feature based classifier with feature level fusion , 1997 .

[29]  Yiding Wang,et al.  Recognition of high-resolution ground targets , 1997, Defense, Security, and Sensing.

[30]  S. Wong.  Multi-look fusion identification: a paradigm shift from quality to quantity in data samples , 2009, Defense + Commercial Sensing.

[31]  Demetri Psaltis,et al.  Correlation filters for aircraft identification from radar range profiles , 1993 .

[32]  Xun Zhang,et al.  Automatic HRR target recognition based on matrix pencil method and multiresolution neural network , 1997, Defense, Security, and Sensing.

[33]  Firooz A. Sadjadi.  A model based technique for recognizing targets by using millimeter wave radar signatures , 1989 .

[34]  Gerald R. Benitz,et al.  Superresolution HRR ATR with high definition vector imaging , 2001 .

[35]  Haitao Liang,et al.  SVM Target Identification Method Based on HRRP Sample Partition , 2007 .

[36]  Clayton V. Stewart,et al.  Comparison of classification approaches for high-range resolution radar , 1992, Defense, Security, and Sensing.

[37]  Hsueh-Jyh Li,et al.  Using range profiles as feature vectors to identify aerospace objects , 1993 .