Studies on Single Observer Passive Location Tracking Algorithm Based on LMS-PF

  • Jing-bo He
  • Sheng-liang Hu
  • Zhong Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 107)


As the emitter’s velocity is given, it could be located by single observer. According to the tracking convergence fast specialty of the linear minimum mean-square error filter and the tracking accuracy specialty of the particle filter, a new passive location algorithm based on a LMS-PF is presented. It is compared with linear minimum mean-square error filtering and extended kalman filtering in passive location. It is proved that the location error by the algorithm is less than by other algorithms.


Particle filtering Linear minimum mean-square error filtering Extended Kalman filtering Passive location 


  1. 1.
    Bar-Shalom Y (1993) Estimation and tracking, principles, techniques, and software. Artech House, BostonMATHGoogle Scholar
  2. 2.
    Bell M, Cathey W (1993) The iterated Kalman filter update as a Gauss-Newton method. IEEE Trans Autom Control 38(2):294–297CrossRefMATHMathSciNetGoogle Scholar
  3. 3.
    Song TL, Speyer J (1985) A stochastic analysis of a modified gain extended Kalman filter with application to estimation with bearing only measurements. IEEE Trans Autom Control 30(10):940–949CrossRefMATHGoogle Scholar
  4. 4.
    Galkowski P, Islam M (1991) An alternative derivation of modified gain function of Song and Speyer. IEEE Trans Autom Control 36(11):1322–1326CrossRefMathSciNetGoogle Scholar
  5. 5.
    Doucet A, Godsill SJ, Andrieu C (2000) On sequential simulation-based methods for Bayesian filtering. Statist Comput 10(3):197–208CrossRefGoogle Scholar
  6. 6.
    Doucet A, de Freitas N, Gordon N (2001) Sequential Monte Carlo methods in practice. Spring-Verlag, New YorkMATHGoogle Scholar
  7. 7.
    Gilks W, Richardson S, Spiegelhalter D (1996) Markov chain Monte Carlo in practice. Chapman & Hall, LondonMATHGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Electronics Engineering CollegeNaval University of EngineeringWuhanChina

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