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Proceedings Paper

Sensor bias estimation in the presence of data association uncertainty
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Paper Abstract

This paper considers the problem of dynamic residual bias estimation in the presence of measurement association uncertainty using common targets of opportunity under a decentralized information processing architecture i.e. independent trackers at each sensor. This is done by extending the scope of the synchronous version of the bias estimation algorithm presented by Lin, Bar-Shalom and Kirubarajan in "Multisensor-Multitarget Bias Estimation for General Asynchronous Sensors" to develop approaches to bias estimation in the presence of measurement association uncertainty. We consider the computational complexity and the sensor-to-fusion-center communication requirements of each of these approaches and compare their simulated performance in terms of RMSE and consistency. Though the simulations are performed with synchronous polar measurements having additive biases, the algorithm may easily be extended to the case with asynchronous measurements in other coordinate systems having both additive and multiplicative biases.

Paper Details

Date Published: 4 September 2009
PDF: 22 pages
Proc. SPIE 7445, Signal and Data Processing of Small Targets 2009, 74450P (4 September 2009); doi: 10.1117/12.828785
Show Author Affiliations
David F. Crouse, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)
Peter Willett, Univ. of Connecticut (United States)


Published in SPIE Proceedings Vol. 7445:
Signal and Data Processing of Small Targets 2009
Oliver E. Drummond; Richard D. Teichgraeber, Editor(s)

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