@Article{cmes.2022.020545, AUTHOR = {Qingdong Wu, Chenxi Li, Tao Shen, Yuan Xu,3}, TITLE = {Improved Adaptive Iterated Extended Kalman Filter for GNSS/INS/UWB-Integrated Fixed-Point Positioning}, JOURNAL = {Computer Modeling in Engineering \& Sciences}, VOLUME = {134}, YEAR = {2023}, NUMBER = {3}, PAGES = {1761--1772}, URL = {http://www.techscience.com/CMES/v134n3/49728}, ISSN = {1526-1506}, ABSTRACT = {To provide stable and accurate position information of control points in a complex coastal environment, an adaptive iterated extended Kalman filter (AIEKF) for fixed-point positioning integrating global navigation satellite system, inertial navigation system, and ultra wide band (UWB) is proposed. In this method, the switched global navigation satellite system (GNSS) and UWB measurement are used as the measurement of the proposed filter. For the data fusion filter, the expectation-maximization (EM) based IEKF is used as the forward filter, then, the Rauch-Tung-Striebel smoother for IEKF filter’s result smoothing. Tests illustrate that the proposed AIEKF is able to provide an accurate estimation.}, DOI = {10.32604/cmes.2022.020545} }