Mobile Tracking in Mixed Line-of-Sight/Non-Line-of-Sight Conditions: Algorithm and Theoretical Lower Bound

Liang Chen, Simo Ali-Löytty, Robert Piche, Lenan Wu

    Research output: Contribution to journalArticleScientificpeer-review

    23 Citations (Scopus)
    57 Downloads (Pure)

    Abstract

    The paper investigates the problem of mobile tracking in mixed line-of-sight (LOS)/non-line-of-sight (NLOS) conditions. The motion of mobile station is modeled by a dynamic white noise acceleration model, while the measurements are time of arrival (TOA). A first-order Markov model is employed to describe the dynamic transition of LOS/NLOS conditions. An improved Rao-Blackwellized particle filter (RBPF) is proposed, in which the LOS/NLOS sight conditions are estimated by particle filtering using the optimal trial distribution, and the mobile state is computed by applying approximated analytical methods. The theoretical error lower bound is further studied in the described problem. A new method is presented to compute the posterior Cramer-Rao lower bound (CRLB): the mobile state is first estimated by decentralized extended Kalman filter (EKF) method, then sigma point set and unscented transformation are applied to calculate Fisher information matrix (FIM). Simulation results show that the improved RBPF is more accurate than current methods, and its performance approaches to the theoretical bound.
    Translated title of the contributionMobile Tracking in Mixed Line-of-Sight/Non-Line-of-Sight Conditions: Algorithm and Theoretical Lower Bound
    Original languageEnglish
    Pages (from-to)753-771
    JournalWIRELESS PERSONAL COMMUNICATIONS
    Volume65
    Issue number4
    DOIs
    Publication statusPublished - 2012
    Publication typeA1 Journal article-refereed

    Publication forum classification

    • Publication forum level 1

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