Dr. David M. Slater Profile

Dr. David M. Slater

at MITRE Corp

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Proceedings Article | 23 May 2013 Paper

Evaluating detection and estimation capabilities of magnetometer-based vehicle sensors

David Slater, Garry Jacyna

Proceedings Volume 8745, 87450A (2013) https://doi.org/10.1117/12.2018512

KEYWORDS: Magnetometers, Sensors, Magnetism, Unattended ground sensors, Magnetic sensors, Roads, Algorithm development, Modeling and simulation, Sensor networks, Infrared sensors

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In an effort to secure the northern and southern United States borders, MITRE has been tasked with developing Modeling and Simulation (M&S) tools that accurately capture the mapping between algorithm-level Measures of Performance (MOP) and system-level Measures of Effectiveness (MOE) for current/future surveillance systems deployed by the the Customs and Border Protection Office of Technology Innovations and Acquisitions (OTIA). This analysis is part of a larger M&S undertaking. The focus is on two MOPs for magnetometer-based Unattended Ground Sensors (UGS). UGS are placed near roads to detect passing vehicles and estimate properties of the vehicle’s trajectory such as bearing and speed. The first MOP considered is the probability of detection. We derive probabilities of detection for a network of sensors over an arbitrary number of observation periods and explore how the probability of detection changes when multiple sensors are employed. The performance of UGS is also evaluated based on the level of variance in the estimation of trajectory parameters. We derive the Cramer-Rao bounds for the variances of the estimated parameters in two cases: when no a priori information is known and when the parameters are assumed to be Gaussian with known variances. Sample results show that UGS perform significantly better in the latter case.

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