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LOCA
2009
Springer

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

14 years 7 months ago
Position Estimation from UWB Pseudorange and Angle-of-Arrival: A Comparison of Non-linear Regression and Kalman Filtering
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.
Kavitha Muthukrishnan, Mike Hazas
Added 27 May 2010
Updated 27 May 2010
Type Conference
Year 2009
Where LOCA
Authors Kavitha Muthukrishnan, Mike Hazas
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