Share Email Print
cover

Proceedings Paper

Recognizing occluded MSTAR targets
Author(s): Bir Bhanu; Grinnell Jones
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

This paper presents an approach for recognizing occluded vehicle targets in Synthetic Aperture Radar (SAR) images. Using quasi-invariant local features, SAR scattering center locations and magnitudes, a recognition algorithm is presented that successfully recognizes highly occluded versions of actual vehicles from the MSTAR public data. Extensive experimental results are presented to show the effect of occlusion on recognition performance in terms of Probability of Correct Identification, Receiver Operating Characteristic (ROC) curves and confusion matrices. The effect of occlusion on performance of this recognition algorithm is accurately predicted. Combined effects such as occlusion and measured positional noise, as well as occlusion and other observed extended operating conditions (e.g., articulation) are also addressed. Although excellent forced recognition results can be achieved at very high (70%) occlusion, practical limitations are found due to the similarity of unoccluded confuser vehicles to highly occluded targets.

Paper Details

Date Published: 24 August 2000
PDF: 9 pages
Proc. SPIE 4053, Algorithms for Synthetic Aperture Radar Imagery VII, (24 August 2000); doi: 10.1117/12.396348
Show Author Affiliations
Bir Bhanu, Univ. of California/Riverside (United States)
Grinnell Jones, Univ. of California/Riverside (United States)


Published in SPIE Proceedings Vol. 4053:
Algorithms for Synthetic Aperture Radar Imagery VII
Edmund G. Zelnio, Editor(s)

© SPIE. Terms of Use
Back to Top