Position Estimation from UWB Pseudorange and Angle-of-Arrival: A Comparison of Non-linear Regression and Kalman Filtering

K. Kavitha Muthukrishnan, M. Hazas

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

    15 Citations (Scopus)
    301 Downloads (Pure)

    Abstract

    This paper presents two algorithms, non-linear regression and Kalman filtering, that fuse heterogeneous data (pseudorange and angle-of-arrival) from an ultra-wideband positioning system. The performance of both the algorithms is evaluated using real data from two deployments, for both static and dynamic scenarios. We also consider the effectiveness of the proposed algorithms for systems with reduced infrastructure (lower deployment density), and for lower-complexity sensing platforms which are only capable of providing either pseudorange or angle-of-arrival.
    Original languageUndefined
    Title of host publicationFourth International Symposium on Location and Context Awareness (LoCA 2009), Co-located with Pervasive09
    EditorsA. Quigley, T. Choudhury
    Place of PublicationBerlin Heidelberg
    PublisherSpringer
    Pages222-239
    Number of pages18
    ISBN (Print)3-642-01720-7
    DOIs
    Publication statusPublished - 7 May 2009
    EventFourth International Symposium on Location and Context Awareness (LoCA 2009), Co-located with Pervasive09 - Tokyo, Japan
    Duration: 7 May 20098 May 2009

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag

    Workshop

    WorkshopFourth International Symposium on Location and Context Awareness (LoCA 2009), Co-located with Pervasive09
    Period7/05/098/05/09
    Other7-8 May 2009

    Keywords

    • EWI-15192
    • METIS-263767
    • IR-65419

    Cite this