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Proceedings Paper

Statistical efficiency of composite position measurements from passive sensors
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Paper Abstract

Combining line-of-sight (LOS) measurements from passive sensors (e.g., satellite-based IR, ground-based cameras, etc.), assumed to be synchronized, into a single composite Cartesian measurement (full position in 3D) via maximum likelihood (ML) estimation, can circumvent the need for nonlinear filtering. This ML estimate is shown to be statistically efficient, and as such, the covariance matrix obtainable from the Cramer-Rao lower bound provides a consistent measurement noise covariance matrix for use in a target tracking filter.

Paper Details

Date Published: 5 May 2011
PDF: 11 pages
Proc. SPIE 8050, Signal Processing, Sensor Fusion, and Target Recognition XX, 805008 (5 May 2011); doi: 10.1117/12.883045
Show Author Affiliations
Richard W. Osborne III, Univ. of Connecticut (United States)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 8050:
Signal Processing, Sensor Fusion, and Target Recognition XX
Ivan Kadar, Editor(s)

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