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Proceedings Paper

Observability of sensor biases using multiple track reports
Author(s): Paul F. Easthope
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Paper Abstract

This paper examines the determination of sensor biases by comparing multiple track outputs from spatially disparate platforms. In many cases, this can be achieved using least- square methods, minimizing the summed-squares of track differences. This method, while simple, is shown to provide valuable information converging the observability of a given type of bias. Observability is here defined as permitting the determination of a unique value for that bias, for each sensor in a pair, given sufficient measurements pairs. For the purposes of this study, the types of bias are divided into three main classes: measurement, own-position and alignment. In general, only members of the first group are individually observable, while for the other two classes observable, while for the other two classes observable combinations of the individual biases can be derived. The least-squares method also provides an effective method for assessing observability in practice, and in determining which estimated biases are most reliable in such circumstances.

Paper Details

Date Published: 4 October 1999
PDF: 12 pages
Proc. SPIE 3809, Signal and Data Processing of Small Targets 1999, (4 October 1999); doi: 10.1117/12.364032
Show Author Affiliations
Paul F. Easthope, Advanced System Architectures Ltd. (United Kingdom)


Published in SPIE Proceedings Vol. 3809:
Signal and Data Processing of Small Targets 1999
Oliver E. Drummond, Editor(s)

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