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Proceedings Paper

Efficient multisensor resource management using Cramer-Rao lower bounds
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Paper Abstract

This paper describes the development of a general framework for the efficient management of multiple sensors in target tracking. The basis of the technique is to quantify, and subsequently control, the accuracy of target state estimation. The Posterior Cramer-Rao lower bound provides the means of achieving this aim by enabling us to determine a bound on the performance of all unbiased estimators of the unknown target state. The general approach is then to use optimization techniques to control the measurement process in order to achieve accurate target state estimation. We are concerned primarily with the deployment and utilization of a limited sensor resource. We also allow for measurement origin uncertainty, with sensor measurements either target generated or false alarms. We exploit previous work to determine a general expression for the Fisher Information Matrix in this case. We show that by making certain assumptions we can express the measurement uncertainty as a constant information reduction factor. This enables the Fisher Information Matrix to be calculated quickly, allowing Cramer-Rao bounds to be utilized for real-time, online sensor management.

Paper Details

Date Published: 7 August 2002
PDF: 16 pages
Proc. SPIE 4728, Signal and Data Processing of Small Targets 2002, (7 August 2002); doi: 10.1117/12.478520
Show Author Affiliations
Marcel L. Hernandez, QinetiQ (United Kingdom)
Thiagalingam Kirubarajan, McMaster Univ. (Canada)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 4728:
Signal and Data Processing of Small Targets 2002
Oliver E. Drummond, Editor(s)

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