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15192 Position Estimation from UWB Pseudorange and Angle-of-Arrival: A Comparison of Non-linear Regression and Kalman Filtering
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Muthukrishnan, K. and Hazas, M. (2009) Position Estimation from UWB Pseudorange and Angle-of-Arrival: A Comparison of Non-linear Regression and Kalman Filtering. In: Fourth International Symposium on Location and Context Awareness (LoCA 2009), Co-located with Pervasive09, 7-8 May 2009, Tokyo, Japan. pp. 222-239. Lecture Notes in Computer Science. Springer Verlag. ISBN 3-642-01720-7

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Official URL: http://dx.doi.org/10.1007/978-3-642-01721-6_14

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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.

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-PS: Pervasive Systems
Research Program:CTIT-WiSe: Wireless and Sensor Systems
Research Project:Smart Surroundings
ID Code:15192
Status:Published
Deposited On:12 March 2009
Refereed:Yes
International:Yes
More Information:statisticsmetis

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