Multipath Cluster-Assisted Single Station Localization Based on SSA-GA in Outdoor NLOS Environment

Abstract

In this paper, we propose a novel multipath cluster-assisted single station localization method based on a genetic algorithm-based improved salp swarm algorithm (SSA-GA) to improve localization accuracy in an outdoor non-line-of-sight (NLOS) propagation environment. The scattering area model is presented which scatterers are considered Gaussian distribution for outdoor NLOS environments. The geometrical properties of propagation paths, such as angle of arrival and time of arrival, are jointly utilized to construct pseudoscatterer distribution. In order to filter the interference scatterers distributed outside the scattering region, the Gaussian kernel-based algorithm is developed. Furthermore, SSA-GA is proposed to solve the positioning objective functions constructed by pseudoscatterers clustering accurately. Results confirm the practicability of our newly proposed method, and the positioning error is less than 5% in outdoor NLOS propagation environment.