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Proceedings Paper

Multisensor data fusion for mine detection
Author(s): Syama P. Chaudhuri; Alan L. Crandall; Denis M. Reidy
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Paper Abstract

This paper demonstrates the advantages of applying raultisensor data fusion techniques for the mine detection and classification problem. It has long been recognized that no single sensor technique is adequate for the detection and classification of the wide spectrum of anti-personnel, anti-vehicle and anti-tank mines currently deployed under an even wider spectrum of battle and geological conditions. The experimental results have indicated that mine detection and classification performance can be greatly enhanced by using an array of complementary sensors whose outputs are fused to extract information not otherwise available from a single sensor.

Paper Details

Date Published: 1 October 1990
PDF: 18 pages
Proc. SPIE 1306, Sensor Fusion III, (1 October 1990); doi: 10.1117/12.21624
Show Author Affiliations
Syama P. Chaudhuri, Sensor Data Integration, Inc. (United States)
Alan L. Crandall, Geo-Centers, Inc. (United States)
Denis M. Reidy, Geo-Centers, Inc. (United States)


Published in SPIE Proceedings Vol. 1306:
Sensor Fusion III
Robert C. Harney, Editor(s)

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