Robust Localization of Signal Source Based on Information Fusion

A robust algorithm for locating the signal source is proposed based on information fusion from different domains to improve the passive localization accuracy under the non-line-of-sight (NLoS) environment. The localization scenario is established by utilizing the information about energy domain, time domain, and frequency domain. The Cramer-Rao lower bounds are derived, and the performance improvement is proved in different domains. By substituting NLoS bias with the statistical average, the localization equations of information fusion are established. A nonconvex localization problem is transformed into a generalized trust domain subproblem by introducing the squared range and the weighted least squares. The position and velocity of the source are obtained by using the bisection procedure. An iterative method is used to estimate the NLoS deviation and refine the position accuracy simultaneously. Simulation results demonstrate the efficiency and robustness of the proposed algorithm.

I. Introduction

With the rapid development of the fifth-generation (5G) wireless communications and Internet of Things (IoT), the information services based on precise localization are increasingly developed in order to provide users diverse services with high quality of experience (QoE) [1], [2]. The localization technology of the radiation source exploits the data fusion of the known information about the scenario and parameters of the received signals to obtain the precise coordinates of the source, which is widely used in the information and communication areas [3]. To provide accurate position service, many studies and applications have been performed to meet the requirement, such as rescue, detection, and safeguard [4].