Passive position location using Bayes' conditional density filter

Subhash Challa; Farhan A. Faruqi

doi:10.1117/12.277221

26 June 1997 Passive position location using Bayes' conditional density filter

Subhash Challa, Farhan A. Faruqi

Proceedings Volume 3087, Navigation and Control Technologies for Unmanned Systems II; (1997) https://doi.org/10.1117/12.277221
Event: AeroSense '97, 1997, Orlando, FL, United States

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.

Citation Download Citation

Subhash Challa and Farhan A. Faruqi "Passive position location using Bayes' conditional density filter", Proc. SPIE 3087, Navigation and Control Technologies for Unmanned Systems II, (26 June 1997); https://doi.org/10.1117/12.277221

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