Automatic target detection, acquisition, and  tracking via hierarchical pattern recognition

Thomas W. Jewitt

doi:10.1117/12.2321788

1 October 1990 Automatic target detection, acquisition, and tracking via hierarchical pattern recognition

Thomas W. Jewitt

Proceedings Volume 1305, Signal and Data Processing of Small Targets 1990; (1990) https://doi.org/10.1117/12.2321788
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

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.

Citation Download Citation

Thomas W. Jewitt "Automatic target detection, acquisition, and tracking via hierarchical pattern recognition", Proc. SPIE 1305, Signal and Data Processing of Small Targets 1990, (1 October 1990); https://doi.org/10.1117/12.2321788

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