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.


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    Title :

    Passive position location using Bayes' conditional density filter


    Contributors:
    Challa, S. (author) / Faruqi, F.A. (author)


    Publication date :

    1997


    Size :

    10 Seiten, 11 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Passive position location using Bayes' conditional density filter [3087-07]

    Challa, S. / Faruqi, F. A. / SPIE | British Library Conference Proceedings | 1997



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    Jaulin, Luc | Wiley | 2019