1 April 2003 Signal-to-clutter measure for measuring automatic target recognition performance using complimentary eigenvalue distribution analysis
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The performance of an automatic target recognition (ATR) algorithm is not only influenced by the relevance of the prior (training) information, but also by the level of difficulty posed by the clutter that surrounds the target. Thus, an objective measure of target- (or signal-) to-clutter ratio (SCR) is important for the assessment of ATRs. We describe a new metric for SCR based on an eigen analysis of a two-class problem. It is believed that an SCR metric, along with a measure for the relevancy of the training data, are the key parameters for the characterization of ATR performance. Various examples are given to illustrate the application of eigen analysis in determining the difficulty level of finding a particular target in the presence of clutter, and consequently how this new SCR metric defines the potential for false alarms.
©(2003) Society of Photo-Optical Instrumentation Engineers (SPIE)
Abhijit Mahalanobis, S. Richard F. Sims, and Alan J. Van Nevel "Signal-to-clutter measure for measuring automatic target recognition performance using complimentary eigenvalue distribution analysis," Optical Engineering 42(4), (1 April 2003). https://doi.org/10.1117/1.1556012
Published: 1 April 2003
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Cited by 16 scholarly publications.
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KEYWORDS
Automatic target recognition

Target detection

Detection and tracking algorithms

Matrices

Optical engineering

Statistical analysis

Optical filters

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