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Proceedings Paper

Learning a detection map for a network of unattended ground sensors
Author(s): Mark W. Koch; Hung D. Nguyen
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Paper Abstract

We have developed algorithms to automatically learn a detection map of a deployed sensor field for a virtual presence and extended defense (VPED) system without apriori knowledge of the local terrain. The VPED system is an unattended network of sensor pods, with each pod containing acoustic and seismic sensors. Each pod has the ability to detect and classify moving targets at a limited range. By using a network of pods we can form a virtual perimeter with each pod responsible for a certain section of the perimeter. The site's geography and soil conditions can affect the detection performance of the pods. Thus, a network in the field may not have the same performance as a network designed in the lab. To solve this problem we automatically estimate a network's detection performance as it is being installed at a site by a mobile deployment unit (MDU). The MDU will wear a GPS unit, so the system not only knows when it can detect the MDU, but also the MDU's location. In this paper, we demonstrate how to handle anisotropic sensor-configurations, geography, and soil conditions.

Paper Details

Date Published: 7 May 2010
PDF: 10 pages
Proc. SPIE 7693, Unattended Ground, Sea, and Air Sensor Technologies and Applications XII, 76930N (7 May 2010); doi: 10.1117/12.849454
Show Author Affiliations
Mark W. Koch, Sandia National Labs. (United States)
Hung D. Nguyen, Sandia National Labs. (United States)


Published in SPIE Proceedings Vol. 7693:
Unattended Ground, Sea, and Air Sensor Technologies and Applications XII
Edward M. Carapezza, Editor(s)

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