Improved Kalman filtering algorithms for mobile tracking in NLOS scenarios

Kegen Yu*, Eryk Dutkiewicz

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

    13 Citations (Scopus)

    Abstract

    This paper presents an improved positioning approach for cellular-network based mobile tracking in severe non-line-of-sight (NLOS) propagation environments. The proposed approach consists of two stages: the smoothing stage to suppress the NLOS errors in the distance measurements; and the position tracking stage. An improved distance smoothing method is proposed to significantly reduce the NLOS errors. It applies online distance mean and variance estimates to identify LOS and NLOS propagations. The online LOS and NLOS identification results, the distance mean and variance estimates are employed to update the Kalman filter (KF) for smoothing distance measurements. A data fusion technique is developed to combine distance measurements, mobile velocity and heading angle estimates provided by motion sensors through the extended KF. Simulation results demonstrate that the proposed two-stage approach significantly improves position accuracy compared to the existing NLOS mitigation algorithms, at the cost of increased computational complexity.

    Original languageEnglish
    Title of host publication2012 IEEE Wireless Communications and Networking Conference, WCNC 2012
    Place of PublicationPiscataway, NJ
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages2390-2394
    Number of pages5
    ISBN (Electronic)9781467304375
    ISBN (Print)9781467304368
    DOIs
    Publication statusPublished - 2012
    Event2012 IEEE Wireless Communications and Networking Conference, WCNC 2012 - Paris, France
    Duration: 1 Apr 20124 Apr 2012

    Other

    Other2012 IEEE Wireless Communications and Networking Conference, WCNC 2012
    CountryFrance
    CityParis
    Period1/04/124/04/12

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