Paper
10 June 1996 SAR ATR via pose-tagged partial evidence fusion
Barry K. Hill, David Cyganski, Richard F. Vaz
Author Affiliations +
Abstract
This paper discusses the development and construction of a new system for robust, obscured object recognition by means of partial evidence reconstruction from object restricted measures. This new approach employs a partial evidence accrual approach to form both an object identity metric and an object pose estimate. The partial evidence information is obtained by applying several instances of the authors' linear signal decomposition/direction of arrival (LSD/DOA) pose estimation technique. LSD/DOA is a means for estimating object pose for possibly articulated objects with multiple degrees of pose freedom that avoids the use of search mechanisms and template matching. Each instance of application of the LSD/DOA system results in a pose estimate and match metric aimed at recognition of a portion of a desired target. Each such partial object recognizer is formed in such a way as to be exposed to no clutter input when positioned over the target component of interest when no obscuration of the target is present. This work was motivated by the fact that pose estimation in the LSD/DOA method is primarily degraded in practice by the presence of background clutter in the pose estimation filter's region of support. By exploiting several independent pose estimators based upon LSD/DOA's reciprocal basis set filters constructed for overlapping sub-regions of the object, we can construct a pose estimate that is independent of clutter in the unobscured case, and robust with respect to obscuration. Results presented here include receiver operating characteristic curves for SAR targets embedded in clutter with and without partial obscuration.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Barry K. Hill, David Cyganski, and Richard F. Vaz "SAR ATR via pose-tagged partial evidence fusion", Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); https://doi.org/10.1117/12.242039
Lens.org Logo
CITATIONS
Cited by 3 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Automatic target recognition

Target recognition

Synthetic aperture radar

Systems modeling

Image processing

Target detection

Data modeling

Back to Top