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Proceedings Paper

Distributed sensor fusion with network constraints
Author(s): Xuezhi Wang; Rob Evans; Jonathan Legg
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Paper Abstract

In a practical multi-sensor tracking network, the sensor data processors communicate only a subset of the data available from each sensor, usually in the form of tracks due to constraints in the communications bandwidth. This paper investigates source coding methods by which track information may be communicated with varying levels of available bandwidth with the aim of minimizing the number of bits required by the fusion center for a given estimation error. In particular, we have formulated the distributed sensor fusion problem subject to network constraints as a minimization problem in terms of the Kullback-Leibler distance (KLD). We have shown that for the multi-sensor track fusion problem, the global KLD will be minimized when the individual, local KLDs are minimized. The solutions to some special cases are derived and the losses in the accuracy of the target state estimates that result from the process of source coding and subsequent interpretation is also determined. Simulated results demonstrate the consistency between both theoretical and practical results.

Paper Details

Date Published: 9 August 2004
PDF: 12 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.541954
Show Author Affiliations
Xuezhi Wang, Univ. of Melbourne (Australia)
Rob Evans, Univ. of Melbourne (Australia)
Jonathan Legg, Defense Science Technology Organization (Australia)

Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)

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