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

Muthukrishnan, Kavitha and Hazas, Michael (2009) Position Estimation from UWB Pseudorange and Angle-of-Arrival: A Comparison of Non-linear Regression and Kalman Filtering. In: Location and Context Awareness 4th International Symposium, LoCA 2009 Tokyo, Japan, May 7-8, 2009 Proceedings. Lecture Notes in Computer Science . Springer, Berlin, pp. 222-239. ISBN 978-3-642-01720-9

Full text not available from this repository.

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:
Contribution in Book/Report/Proceedings
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/qa75
Subjects:
ID Code:
59099
Deposited By:
Deposited On:
10 Oct 2012 15:06
Refereed?:
Yes
Published?:
Published
Last Modified:
10 Nov 2020 11:03