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Proceedings Paper

Passive position location using Bayes' conditional density filter
Author(s): Subhash Challa; Farhan A. Faruqi
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Paper Abstract

Passive position location using bearings only information is a classical navigation problem, Various methods proposed to date use either triangulation or circulation rules in nonlinear filtering framework; like nonlinear least squares filtering method providing approximate maximum likelihood estimates and extended Kalman filtering method providing approximate minimum variance estimates. Both are approximate filters due to inherent linearization in these methods. A completely optimal nonlinear filter, referred to as Bayes' conditional density filter is presented in this paper. This method is not subjected to any linearization mechanisms as in other methods currently in use. However, the method is subjected to increased computational burden.

Paper Details

Date Published: 26 June 1997
PDF: 10 pages
Proc. SPIE 3087, Navigation and Control Technologies for Unmanned Systems II, (26 June 1997); doi: 10.1117/12.277221
Show Author Affiliations
Subhash Challa, Queensland Univ. of Technology (Australia)
Farhan A. Faruqi, Queensland Univ. of Technology (Australia)


Published in SPIE Proceedings Vol. 3087:
Navigation and Control Technologies for Unmanned Systems II
Scott A. Speigle, Editor(s)

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