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This paper proposes two efficient and easy-to-use error mitigation solutionsto the problem of three-dimensional (3-D) angle-of-arrival (AOA) sourcelocalization in the mixed line-of-sight (LOS) and non-line-of-sight (NLOS)indoor environments. A weighted linear least squares estimator is derived firstfor the LOS AOA components in terms of the direction vectors of arrival, albeitin a sub-optimal manner. Next, data selection exploiting the sum of squaredresiduals is carried out to discard the error-prone NLOS connections. In sodoing, the first approach is constituted and more accurate closed-form locationestimates can be obtained. The second method applies a simulated annealingstochastic framework to realize the robust $\ell_1$-minimization criterion,which therefore falls into the methodology of statistical robustification.Computer simulations and ultrasonic onsite experiments are conducted toevaluate the performance of the two proposed methods, demonstrating theiroutstanding positioning results in the respective scenarios.

Two Efficient and Easy-to-Use NLOS Mitigation Solutions to Indoor 3-D AOA-Based Localization