Mr. Saipradeep Venkatraman Profile

Saipradeep Venkatraman

at Univ of Cincinnati

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Proceedings Article | 6 August 2003 Paper

Multipath-aided location estimation using angles of arrival

Saipradeep Venkatraman, James Caffery

Proceedings Volume 5084, (2003) https://doi.org/10.1117/12.498227

KEYWORDS: Non-line-of-sight propagation, Commercial off the shelf technology, Antennas, Computer simulations, Factor analysis, Scattering, Telecommunications, Error analysis, Wireless communications, Radio propagation

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Angles of arrival (AOAs) of a signal transmitted by a mobile station (MS) are estimated at two or more base stations (BSs) by employing directive antennas or antenna arrays. In traditional location algorithms, the MS position is determined by solving for the intersecting points of at least two lines of position given by these angles and the known positions of the BSs or using a Taylor series (TS) based algorithm to get a least squares (LS) solution. Obstruction of the direct path leading to non-line-of-sight (NLOS) propagation and the presence of multipaths due to scattering objects near and around the MS and BSs lead to errors in the measured AOAs that cause these algorithms to perform poorly. In this paper, we propose an algorithm that makes use of AOA measurements at only 3 BSs including the serving BS. The algorithm mitigates the angular error by computing normalized scale factors or weights that adjust the corrupted angle measurements to near their true values. Utilizing the constraints imposed by the geometry of the cell layout and bounds obtained using the multipath angles, the scale factor estimation is formulated as a constrained optimization problem. Bounds on the scale factors are obtained by making use of the known maximum angular spread at the NLOS BSs and the objective function to be minimized is the angle error norm at the serving BS. Our proposed algorithm has the advantage of not being limited to any particular network and can be adopted universally. Simulations show that the proposed algorithm performs significantly better than the traditional algorithms especially when multipath information is incorporated.

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