Efficient bias reduction approach of time‐of‐flight‐based wireless localisation networks in NLOS states. Issue 11 (17th September 2018)

• Record Type: Journal Article
• Authors: Xiong, Hailiang; Peng, Meixuan; Zhu, Kongfan; Yang, Yang; Du, Zhengfeng; Xu, Hongji; Gong, Shu
• Is Part Of: IET radar, sonar & navigation. Volume 12:Issue 11(2018)
• Page Start: 1353
• Page End: 1360
• Publication Date: 2018-09-17
• Subjects: mobile radio -- indoor radio -- radio networks -- time‐of‐arrival estimation -- indoor communication -- wireless sensor networks -- least squares approximations -- jitter; location accuracy -- Cramer–Rao lower bound is derived -- NLOS error -- utilising novel three‐step weighted linear least squares algorithm -- range‐based expressions -- three‐dimensional wireless cooperative localisation networks -- clock jitter error -- nonline‐of‐sight error -- target location -- time of flight -- efficient bias mitigation algorithm -- NLOS states -- time‐of‐flight‐based wireless localisation networks -- efficient bias reduction approach -- state‐of‐the‐art approaches -- positioning accuracy; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2018.5167
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : An efficient bias mitigation algorithm based on time of flight is proposed for positioning the target location and reducing the non‐line‐of‐sight (NLOS) error and clock jitter error in three‐dimensional wireless cooperative localisation networks. Through linearising the range‐based expressions and utilising novel three‐step weighted linear least squares algorithm, an algebraic solution of target can be derived, in which the clock jitter error and NLOS error can be alleviated effectively. Meanwhile, the Cramer–Rao lower bound (CRLB) is derived for the standard of performance evaluation. The location accuracy of the proposed algorithm is analysed and compared with the conventional methods through simulation experiment. The simulation results indicate that the precision of the proposed algorithm can approach the CRLB, what is more, the proposed algorithm can provide obvious improvements in positioning accuracy compared to the state‐of‐the‐art approaches.