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Proceedings Paper

Multisensor fusion for improved air-to-ground target localization
Author(s): Moira I. Smith; Eleanor M. Januarius; Mark Bernhardt; David Nicholson; Gareth Rees; Jason F. Ralph
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Paper Abstract

The accuracy with which an object can be localized is key to the success of a targeting system. Localization is generally achieved by a single sensor, most notably Synthetic Aperture Radar (SAR) or an Infra-Red (IR) device, supported by an Inertial Navigation System (INS) and/or a Global Positioning System (GPS). Future targeting systems are expected to contain (or to have access to data from) multiple sensors, thus enabling data fusion to be conducted and an improved estimate of target location to be deduced. This paper presents a sensor fusion testbed for fusing data from multiple sensors. Initially, a simple, optimal static fusion scheme is illustrated, then focusing on air-to-ground targeting applications example results are given for single and multiple platform sorties involving a variety of sensor combinations. Consideration is given to the most appropriate sensor mix across single and multiple aircraft, as well as architectural implementation issues and effects. The sensitivity of the fusion method to key parameters is then discussed before some conclusions are drawn about the behavior, implications and benefit of this approach to improving targeting.

Paper Details

Date Published: 16 August 2001
PDF: 11 pages
Proc. SPIE 4380, Signal Processing, Sensor Fusion, and Target Recognition X, (16 August 2001); doi: 10.1117/12.436971
Show Author Affiliations
Moira I. Smith, Defence Evaluation and Research Agency Farnborough (United Kingdom)
Eleanor M. Januarius, Defence Evaluation and Research Agency Farnborough (United Kingdom)
Mark Bernhardt, Defence Evaluation and Research Agency Farnborough (United Kingdom)
David Nicholson, BAE Systems (United Kingdom)
Gareth Rees, BAE Systems (United Kingdom)
Jason F. Ralph, Univ. of Liverpool (United Kingdom)


Published in SPIE Proceedings Vol. 4380:
Signal Processing, Sensor Fusion, and Target Recognition X
Ivan Kadar, Editor(s)

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