Paper
4 October 1999 Observability of sensor biases using multiple track reports
Paul F. Easthope
Author Affiliations +
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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paul F. Easthope "Observability of sensor biases using multiple track reports", Proc. SPIE 3809, Signal and Data Processing of Small Targets 1999, (4 October 1999); https://doi.org/10.1117/12.364032
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Cited by 10 scholarly publications.
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KEYWORDS
Sensors

Filtering (signal processing)

Radar

Algorithm development

Berkelium

Error analysis

Matrices

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