Paper
13 July 2000 Evaluation of two-color missile detection algorithms against real backgrounds
Author Affiliations +
Abstract
Missile warning is one of the most significant problems facing aircraft flying into regions of unrest around the world. Recent advances in technology provide new avenues for detecting these threats and have permitted the use of imaging detectors and multi-color systems. Detecting threats while maintaining a low false alarm rate is the most demanding challenge facing these systems. Using data from ARFL's Spectral Infrared Detection System (SIRDS) test bed, the efficacy of alternative spectral threat detection algorithms developed around these technologies are evaluated and compared. The data used to evaluate the algorithms cover a range of clutter conditions including urban, industrial, maritime and rural. Background image data were corrected for non-uniformity and filtered to enhance threat to clutter response. The corrected data were further processed and analyzed statistically to determine probability of detection thresholds and the corresponding probability of false alarm. The results are summarized for three algorithms including simple threshold detection, background normalized analysis, and an inter-band correlation detection algorithm.
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Frank O. Baxley, Richard B. Sanderson, Joel B. Montgomery, and John F. McCalmont "Evaluation of two-color missile detection algorithms against real backgrounds", Proc. SPIE 4048, Signal and Data Processing of Small Targets 2000, (13 July 2000); https://doi.org/10.1117/12.391971
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KEYWORDS
Detection and tracking algorithms

Missiles

Algorithm development

Performance modeling

Statistical analysis

Image filtering

Linear filtering

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