Accurate and reliable localization is crucial for various wireless
communication applications. Numerous studies have proposed accurate
localization methods using hybrid received signal strength (RSS) and angle of
arrival (AOA) measurements. However, these studies typically assume identical
measurement noise distributions for different anchor nodes, which may not
accurately reflect real-world scenarios with varying noise distributions. In
this paper, we propose a simple and efficient localization method based on
hybrid RSS-AOA measurements that accounts for the varying measurement noises of
different nodes. We derive a closed-form estimator for the target location
based on the linear weighted least squares (LWLS) algorithm, with each LWLS
equation weight being the inverse of its residual variance. Due to the unknown
variances of LWLS equation residuals, we employ a two-stage LWLS method for
estimation. The proposed method is computationally efficient, adaptable to
different types of wireless communication systems and environments, and
provides more accurate and reliable localization results compared to existing
RSS-AOA localization techniques. Additionally, we derive the Cramer-Rao Lower
Bound (CRLB) for the RSS-AOA signal sequences used in the proposed method.
Simulation results demonstrate the superiority of the proposed method