Share Email Print

Proceedings Paper

Automatic target detection, acquisition, and tracking via hierarchical pattern recognition
Author(s): Thomas W. Jewitt
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

A hierarchical data structure is presented to organize the various types of informational entities available from infrared (IR) sensor data. This provides a common framework in which to discuss alternate techniques applicable to the problem of automatic acquisition and tracking of small targets. Of these techniques, the Hierarchical Pattern Recognition (HPR) algorithm processes all available information for the acquisition. Targets of interest are typically unresolved by sensor optics at acquisition ranges and appear against highly cluttered background scenes. Performance of the HPR algorithm is demonstrated by simulation using various types of pattern classifiers, with and without the benefit of feature data inputs representing scene context. The Viterbi algorithm is utilized to resolve ambiguous observation-to-track pairings while tracking an acquired target. Its performance is characterized by the expected number of frames required to resolve such ambiguities.

Paper Details

Date Published: 1 October 1990
Proc. SPIE 1305, Signal and Data Processing of Small Targets 1990, (1 October 1990); doi: 10.1117/12.2321788
Show Author Affiliations
Thomas W. Jewitt, Magnavox/General Atronics Corp. (United States)

Published in SPIE Proceedings Vol. 1305:
Signal and Data Processing of Small Targets 1990
Oliver E. Drummond, Editor(s)

© SPIE. Terms of Use
Back to Top