Learning a detection map for a network of unattended ground sensors.

Conference · Mon Mar 01 04:00:00 EST 2010

OSTI ID:988513

Nguyen, Hung D; Koch, Mark William

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.

• Research Organization: Sandia National Laboratories
• Sponsoring Organization: USDOE
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 988513
• Report Number(s): SAND2010-1327C
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
ACOUSTICS
ALGORITHMS
DETECTION
GEOGRAPHY
GLOBAL POSITIONING SYSTEM
LEARNING
PERFORMANCE
SECURITY
SOILS
TARGETS