Paper
4 September 2009 Sensor bias estimation in the presence of data association uncertainty
Author Affiliations +
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.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David F. Crouse, Yaakov Bar-Shalom, and Peter Willett "Sensor bias estimation in the presence of data association uncertainty", Proc. SPIE 7445, Signal and Data Processing of Small Targets 2009, 74450P (4 September 2009); https://doi.org/10.1117/12.828785
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Cited by 9 scholarly publications.
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KEYWORDS
Sensors

Detection and tracking algorithms

Target detection

Error analysis

Filtering (signal processing)

Algorithm development

Spherical lenses

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