A Simple and Efficient RSS-AOA Based Localization with Heterogeneous Anchor Nodes

TL;DR

This paper introduces a simple, efficient RSS-AOA localization method that accounts for heterogeneous noise across anchor nodes, improving accuracy and reliability in wireless systems.

Contribution

It presents a novel two-stage LWLS estimator that handles varying measurement noise, with a derived CRLB and demonstrated superior performance over existing techniques.

Findings

The proposed method outperforms existing RSS-AOA localization techniques.

The two-stage LWLS estimator effectively manages different noise variances.

Simulation results confirm improved accuracy and reliability.

Abstract

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.