A Hybrid AOA and TDOA-Based Localization Method Using Only Two Stations

Xiaolong Li,Yi Xing,Zhenkai Zhang,Atsushi Mase

doi:10.1155/2021/5512395

Abstract

Target localization plays an important role in the application of radar, sonar, and wireless sensor networks. In order to improve the localization performance using only two stations, a hybrid localization method based on angle of arrival (AOA) and time difference of arrival (TDOA) measurements is proposed in this paper. Firstly, the optimization model for localization based on AOA and TDOA are built, respectively, in the sensor network. Secondly,the majorization-minimization (MM) method is employed to create surrogate functions for solving the multiple objective optimization problem. Next, the hybrid localization problem is solved by the projected gradient decent (PGD) method. Finally, the Cramer–Rao lower bound (CRLB) for the joint AOA and TDOA method is derived for the comparison. Simulations proved that the proposed method has improved localization performance using AOA and TDOA measurements from only two base stations.

Highlights

Source localization in the sensor network is a fundamental problem which has received an upsurge of attention in recent years
In order to reduce the sensors for target localization, we propose a hybrid time difference of arrival (TDOA)/angle of arrival (AOA) localization approach only with two sensors, taking advantage of the complementary property between the TDOA- and AOAbased localization methods
In order to prove the effectiveness of the proposed method using only two stations, source localization results using 3 BSs are presented here based on optimization methods, including weighted least squares (WLS-O-3BSs) [7], and optimization using time difference of arrival (TDOA-O-3BSs) [21]. ey are compared with the proposed methods

Summary

Introduction

Source localization in the sensor network is a fundamental problem which has received an upsurge of attention in recent years. Many algorithms have been presented in literature to determine the source position, based on the time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AOA), and received signal strength (RSS) method. Localization problem based on the TOA method in the quasi-synchronous network is addressed in [2], in which a two-step linear algorithm is presented for estimating the passive object position. In [16], RSS localization methods based on convex optimization are presented to solve the noncooperative and cooperative problems in sensor networks. RSS algorithms are based on known exact received signal without multipath effect, and the AOA method can perform well only when the target is not far away from the sensors [17]. E hybrid AOA- and RSS-based localization method is presented in [23] for 3D wireless sensor network without central processor. Bold uppercase (e.g., H) and lowercase (e.g., b) letters represent the matrices and vectors, respectively. e notations (·)T and (·)H stand for transpose and Hermitian of their argument, respectively. ‖ · ‖2 denotes the l2 norm of a vector. e gradient of f at x is denoted by ∇f(x)

Basic Localization Methods Based on TDOA

Hybrid Localization Method Based on AOA and TDOA

R is the Gaussian error variance of

Simulations

Conclusion