Angle Residual-Based NLOS Suppression and Localization Method in Wireless Sensor Networks

With the rapid development of Internet-of-Things (IOT) applications, the performance of existing wireless localization methods under nonline-of-sight (NLOS) transmission environments is seriously challenged. Therefore, this article proposes a new definition of residual, that is, the angle residual. The key target of the angle residual is to detect line-of-sight (LOS) links from measured and calculated angle parameters. The target position is then estimated by a two-step weighted least-squares (TS-WLS) algorithm, where only positioning parameters of LOS links are included. Simulation shows that the proposed algorithm performs better than traditional algorithms, especially when the mobile node (MN) position and the NLOS link distribution are randomly generated. Therefore, the proposed method effectively improves positioning performance and enhances localization stability in real NLOS transmission environments.