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Proceedings Paper

Unified generalized Bayesian accrual of evidence for robust ATR: new results
Author(s): John R. Hoffman; Ronald P. S. Mahler; Ravi Prasanth; Melvyn Huff; Ravi B. Ravichandran; Raman K. Mehra; Stanton Musick
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Paper Abstract

We describe ongoing work in applying Finite Set Statistics (FISST) techniques to a Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) problem. It summarizes recent results in an ongoing project in which we are applying FISST filtering approaches to the problem of identifying ground targets from Synthetic Aperture Radar. The signatures for these targets are ambiguous because of extended operating conditions, that is the images have uncharacterizeable noise introduced in the form of mud, dents, etc. We propose a number of mechanisms for compensating for this noise.

Paper Details

Date Published: 16 August 2001
PDF: 12 pages
Proc. SPIE 4380, Signal Processing, Sensor Fusion, and Target Recognition X, (16 August 2001); doi: 10.1117/12.436940
Show Author Affiliations
John R. Hoffman, Lockheed Martin Tactical Defence Systems (United States)
Ronald P. S. Mahler, Lockheed Martin Tactical Defence Systems (United States)
Ravi Prasanth, Scientific Systems Co., Inc. (United States)
Melvyn Huff, Scientific Systems Co., Inc. (United States)
Ravi B. Ravichandran, Scientific Systems Co., Inc. (United States)
Raman K. Mehra, Scientific Systems Co., Inc. (United States)
Stanton Musick, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 4380:
Signal Processing, Sensor Fusion, and Target Recognition X
Ivan Kadar, Editor(s)

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