Hybrid TOA-AOA estimation error test and non-line of sight identification in wireless location

Authors:
Chin-Der Wann;Han-Yi Lin
Affiliations:
Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, 80424, Taiwan, ROC;Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, 80424, Taiwan, ROC
Venue:
Wireless Communications & Mobile Computing
Year:
2009

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Abstract

In this paper, a modified time-of-arrival (TOA) estimation error test and a hybrid time-of-arrival-angle-of-arrival (TOA-AOA) estimation error test for identification of line of sight (LOS) base stations (BSs) are proposed. The proposed schemes aim to improve the location accuracy of wireless location systems suffering from the non-line of sight (NLOS) propagation errors. The modified TOA-based estimation error test is considered a straightforward approach in identifying the LOS-BS set when the number of LOS BSs is greater than or equal to three. When both TOA and AOA metrics are available, hybrid TOA-AOA squares of normalized estimation errors are formulated by adopting the approximate maximum likelihood (AML) estimation. The proposed hybrid estimation error test scheme is capable of identifying the LOS-NLOS status of each BS, and performing location estimation in the situation where only two LOS BSs exist. Simulation results show that the proposed schemes are capable of correctly identifying the LOS BSs and improving the overall location accuracy. Copyright © 2009 John Wiley & Sons, Ltd. The paper presents a modified time-of-arrival (TOA) estimation error test and a hybrid time-of-arrival-angle-of-arrival (TOA-AOA) estimation error test for identification of line of sight (LOS) base stations. The proposed schemes aim to improve the location accuracy of wireless location systems suffering from the non-line of sight (NLOS) propagation errors. Hybrid TOA-AOA squares of normalized estimation errors are formulated by adopting the approximate maximum likelihood estimation, and used in the estimation error test for identifying the LOS BSs and improving the overall location accuracy.