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Proceedings Paper

Distributed air-to-ground targeting
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Paper Abstract

This paper examines the requirement for accurate estimates of the statistical correlations between measurements in a distributed air-to-ground targeting system. The study uses results from a distributed multi-platform targeting simulation based on a level-1 data fusion system to assess the extent to which correlated measurements can degrade system performance, and the degree to which these effects need to be included to obtain a required level of accuracy. The data fusion environment described in the paper incorporates a range of target tracking and data association algorithms, including several variants of the standard Kalman filter, probabilistic association techniques and Reid's multiple hypothesis tracker. A variety of decentralized architectures are supported, allowing comparison with the performance of equivalent centralized systems. In the analysis, consideration is given to constraints on the computational complexities of the fusion system, and the availability of estimates of the measurement correlations and platform-dependent biases. Particular emphasis is placed on the localisation accuracy achieved by different algorithmic approaches and the robustness of the system to errors in the estimated covariance matrices.

Paper Details

Date Published: 6 March 2002
PDF: 11 pages
Proc. SPIE 4731, Sensor Fusion: Architectures, Algorithms, and Applications VI, (6 March 2002); doi: 10.1117/12.458387
Show Author Affiliations
Jason F. Ralph, Univ. of Liverpool (United Kingdom)
Moira I. Smith, Waterfall Solutions Ltd. (United Kingdom)
Mark Bernhardt, QinetiQ Ltd. (United Kingdom)
Catherine E. West, QinetiQ Ltd. (United Kingdom)
Christopher R. Angell, QinetiQ Ltd. (United Kingdom)
Scott W. Sims, Univ. of Liverpool (United Kingdom)

Published in SPIE Proceedings Vol. 4731:
Sensor Fusion: Architectures, Algorithms, and Applications VI
Belur V. Dasarathy, Editor(s)

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