Exploiting AoA Estimation Accuracy for Indoor Localization: A Weighted AoA-Based Approach

Abstract

For angle-of-arrival (AoA)-based localization methods, the AoA estimation accuracy would notably influence the localization performance. In this letter, we evaluate the estimation accuracy of different AoAs in a multipath environment and propose a weighted AoA-based localization approach. Specifically, the AoA estimation accuracy is quantified by deriving a closed form expression of asymptotic variance of the AoA estimation error. However, in practice, the accessible information for receivers is insufficient to retrieve the variance. Accordingly, we still find an approximate but effective substitution to evaluate the AoA estimation accuracy on basis of the limited information. Aided by the above analysis, we design the weighted localization method, where each estimated AoA is weighted with corresponding factor related to the AoA estimation accuracy. Simulations show that our proposed localization method decreases the median localization error by 20% compared with the unweighted method.