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

Research output: Contribution in Book/Report/ProceedingsPaper

Published

Publication date05/2009
Host publicationLocation and Context Awareness 4th International Symposium, LoCA 2009 Tokyo, Japan, May 7-8, 2009 Proceedings
EditorsTanzeem Choudhury , Aaron Quigley , Thomas Strang , Koji Suginuma
Place of publicationBerlin
PublisherSpringer
Pages222-239
Number of pages18
ISBN (Print)978-3-642-01720-9
Original languageEnglish

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume5561
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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.