title: An Adaptive Low-Cost GNSS/MEMS-IMU Tightly-Coupled Integration System with Aiding Measurement in a GNSS Signal-Challenged Environment.
abstract: The main aim of this paper is to develop a low-cost GNSS/MEMS-IMU tightly-coupled integration system with aiding information that can provide reliable position solutions when the GNSS signal is challenged such that less than four satellites are visible in a harsh environment. To achieve this goal, we introduce an adaptive tightly-coupled integration system with height and heading aiding (ATCA). This approach adopts a novel redundant measurement noise estimation method for an adaptive Kalman filter application and also augments external measurements in the filter to aid the position solutions, as well as uses different filters to deal with various situations. On the one hand, the adaptive Kalman filter makes use of the redundant measurement system's difference sequence to estimate and tune noise variance instead of employing a traditional innovation sequence to avoid coupling with the state vector error. On the other hand, this method uses the external height and heading angle as auxiliary references and establishes a model for the measurement equation in the filter. In the meantime, it also changes the effective filter online based on the number of tracked satellites. These measures have increasingly enhanced the position constraints and the system observability, improved the computational efficiency and have led to a good result. Both simulated and practical experiments have been carried out, and the results demonstrate that the proposed method is effective at limiting the system errors when there are less than four visible satellites, providing a satisfactory navigation solution.
authors.affiliation: Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China. zhouqifanbuaa@gmail.com.|University of Calgary, 2500 University Drive N.W. Calgary, AL T2N1N4, Canada. zhouqifanbuaa@gmail.com.
authors.forename: Qifan
authors.initials: Q
authors.lastname: Zhou
authors.affiliation: Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China. zhanghai@buaa.edu.cn.
authors.forename: Hai
authors.initials: H
authors.lastname: Zhang
authors.affiliation: University of Calgary, 2500 University Drive N.W. Calgary, AL T2N1N4, Canada. liyou331@gmail.com.
authors.forename: You
authors.initials: Y
authors.lastname: Li
authors.affiliation: Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China. bayexx@126.com.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Li
keywords: GPS; MEMS-IMU; adaptive Kalman filter; tightly-coupled integration