Robust HRR radar target identification by hybridization of HMM and eigen-template-based matched filtering

Anindya S. Paul; Arnab Kumar Shaw

doi:10.1117/12.487554

16 September 2003 Robust HRR radar target identification by hybridization of HMM and eigen-template-based matched filtering

Anindya S. Paul, Arnab Kumar Shaw

Author Affiliations +

Proceedings Volume 5094, Automatic Target Recognition XIII; (2003) https://doi.org/10.1117/12.487554
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

In this paper, a new 1-D hybrid Automatic Target Recognition (ATR) algorithm is developed for sequential High Range Resolution (HRR) radar signatures. The proposed hybrid algorithm combines Eigen-Template based Matched Filtering (ETMF) and Hidden Markov modeling (HMM) techniques to achieve superior HRR-ATR performance. In the proposed hybrid approach, each HRR test profile is first scored by ETMF which is then followed by independent HMM scoring. The first ETMF scoring step produces a limited number of "most likely" models that are target and aspect dependent. These reduced number of models are then used for improved HMM scoring in the second step. Finally, the individual scores of ETMF and HMM are combined using Maximal Ratio Combining to render a classification decision. Classification results are presented for the MSTAR data set via ROC curves.

Citation Download Citation

Anindya S. Paul and Arnab Kumar Shaw "Robust HRR radar target identification by hybridization of HMM and eigen-template-based matched filtering", Proc. SPIE 5094, Automatic Target Recognition XIII, (16 September 2003); https://doi.org/10.1117/12.487554

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