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Proceedings Paper

Clutter and target signature statistics from the DARPA background clutter experiment
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Paper Abstract

Clutter is the largest factor contributing to the poor detection rates and high false-alarm rates for mine and unexploded ordnance (UXO) detection systems. The source of this clutter can be either naturally occurring or anthropic. Because the standard detector technologies are anomaly-based systems, few features within the sensor data permit mitigation of false alarms or provide an avenue to enhance detection rates. To achieve operational detection performance, a better understanding of clutter statistics is required at the single pixel level and at the feature level. This paper presents an in-depth assessment of the statistical properties of clutter and target signatures for a specific test site. This assessment uses data collected during the Defense Advanced Research Projects Agency (DARPA) Background Clutter Data Collection Experiment. Pixel-level statistics for electromagnetic induction detection systems are discussed. The resulting statistical distribution functions for clutter and targets exhibit poor separation. Improved separation of the distribution functions is achieved if features are employed. For example, by measuring the particular size and shape features of target signatures, the false-alarm rate can be reduced with minimal decrease in the detection rate. By using feature-level information, improved system performance can be achieved. This improved performance is dependent on the feature-level statistics of a specific site and is always limited by the overlap between the distribution functions of the clutter and target signatures. The resulting performance enhancement -- although significant -- is still far below the level required for very high detection rates and low false- alarm rates.

Paper Details

Date Published: 4 September 1998
PDF: 17 pages
Proc. SPIE 3392, Detection and Remediation Technologies for Mines and Minelike Targets III, (4 September 1998); doi: 10.1117/12.324153
Show Author Affiliations
Erik M. Rosen, Institute for Defense Analyses (United States)
Thomas W. Altshuler, Institute for Defense Analyses (United States)

Published in SPIE Proceedings Vol. 3392:
Detection and Remediation Technologies for Mines and Minelike Targets III
Abinash C. Dubey; James F. Harvey; J. Thomas Broach, Editor(s)

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