1 December 1999 Kullback-Leibler distances for quantifying clutter and models
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We examine metrics for measuring clutter effectiveness on model-based automatic target recognition (ATR) systems with forwardlooking infrared (FLIR) sensors. The measure for clutter effectiveness proposed is the difference of two Kullback-Leibler distances between the idealized approximate probabilistic models without clutter and the real model containing clutter. We establish that occluding objects and clutter, when manipulated, do not present a fundamental challenge to model- based ATR systems if the model manipulated is an accurate representation of the obscuring clutter. However, if the obscurer is not manipulated, performance degrades in cases where the obscurer is an ''effective clutterer. To quantify the effect of clutter in ATR, estimation and detection problems are considered for rigid ground-based targets. For estimating the orientation of a vehicle, the Hilbert-Schmidt distance is employed.
Aaron D. Lanterman, Joseph A. O'Sullivan, and Michael I. Miller "Kullback-Leibler distances for quantifying clutter and models," Optical Engineering 38(12), (1 December 1999). https://doi.org/10.1117/1.602323
Published: 1 December 1999
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Cited by 26 scholarly publications.
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KEYWORDS
Data modeling

Performance modeling

Systems modeling

Automatic target recognition

Target detection

Sensors

Optical engineering

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