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Proceedings Paper

Statistically significant performance results of a mine detector and fusion algorithm from an x-band high-resolution SAR
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Paper Abstract

Current mine detection research indicates that no single sensor or single look from a sensor will detect mines/minefields in a real-time manner at a performance level suitable for a forward maneuver unit. Hence, the integrated development of detectors and fusion algorithms are of primary importance. A problem in this development process has been the evaluation of these algorithms with relatively small data sets, leading to anecdotal and frequently over trained results. These anecdotal results are often unreliable and conflicting among various sensors and algorithms. Consequently, the physical phenomena that ought to be exploited and the performance benefits of this exploitation are often ambiguous. The Army RDECOM CERDEC Night Vision Laboratory and Electron Sensors Directorate has collected large amounts of multisensor data such that statistically significant evaluations of detection and fusion algorithms can be obtained. Even with these large data sets care must be taken in algorithm design and data processing to achieve statistically significant performance results for combined detectors and fusion algorithms. This paper discusses statistically significant detection and combined multilook fusion results for the Ellipse Detector (ED) and the Piecewise Level Fusion Algorithm (PLFA). These statistically significant performance results are characterized by ROC curves that have been obtained through processing this multilook data for the high resolution SAR data of the Veridian X-Band radar. We discuss the implications of these results on mine detection and the importance of statistical significance, sample size, ground truth, and algorithm design in performance evaluation.

Paper Details

Date Published: 21 September 2004
PDF: 10 pages
Proc. SPIE 5415, Detection and Remediation Technologies for Mines and Minelike Targets IX, (21 September 2004); doi: 10.1117/12.542237
Show Author Affiliations
Arnold C. Williams, Science Applications International Corp. (United States)
Peter W. Pachowicz, George Mason Univ. (United States)

Published in SPIE Proceedings Vol. 5415:
Detection and Remediation Technologies for Mines and Minelike Targets IX
Russell S. Harmon; J. Thomas Broach; John H. Holloway, Editor(s)

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