The effects of uncertainty and uncertainty modeling on information-based sensor manager performance

Published

Conference Paper

A proliferation of the number and variety of sensors for the landmine detection problem has created the need for a sensor manager that is able to intelligently task and coordinate the operation of a suite of landmine sensors. Previous work has developed a framework for sensor management that takes into account the context of the landmine detection problem. The sensor manager searches for N targets in a grid using M multimodal sensors by seeking to maximize the expected information gain. The probabilities of detection and false alarm of the sensors are assumed to be known and are used in the sensor manager calculations. However, in a real-world landmine detection setting, the performance characteristics of the sensors will in fact be unknown. Uneven and irregular ground, vegetation, unanticipated clutter objects, even bad weather - all these can affect the performance of a landmine sensor. This paper examines the effects of uncertainty in the probabilities of detection and false alarm on the performance of the previously presented sensor manager and further examines the performance effects of properly and improperly modeling this uncertainty. Performance is, naturally, found to be adversely affected by uncertainty. However, it is demonstrated that properly modeling the uncertainty present in the problem helps to recover some of the performance that is lost through the introduction of uncertainty.

Full Text

Duke Authors

Cited Authors

  • Kolba, MP; Collins, LM

Published Date

  • August 23, 2006

Published In

Volume / Issue

  • 6217 II /

International Standard Serial Number (ISSN)

  • 0277-786X

International Standard Book Number 10 (ISBN-10)

  • 081946273X

International Standard Book Number 13 (ISBN-13)

  • 9780819462732

Digital Object Identifier (DOI)

  • 10.1117/12.665595

Citation Source

  • Scopus