@inproceedings{319f92a7ecef4fe8acaad923608c994e,
title = "An integrated INS/GNSS urban navigation system based on fuzzy adaptive Kalman filter",
abstract = "In the complex urban environments, Land Vehicle Navigation (LVN) system with INS and GNSS has the ever-changing statistical characteristics of the measurement noise due to the complicated road state and the loss of satellite signals caused by obstructions, which will reduce the filtering precision, even cause divergence. To solve this problem, we introduce an integrated INS/GNSS navigation system based on fuzzy adaptive Kalman filter. In this system, the fuzzy inference system is used to constantly adjust the weight of measurement noise covariance matrix through monitoring the difference from the estimated residual to the theoretical one. Then the measurement noise covariance matrix is updating online and approaching the actual one. The result shows that compared with the performance of a Standard Kalman filter (SKF), the proposed fuzzy adaptive Kalman filter gives better results, in terms of accuracy, than the SKF.",
keywords = "Fuzzy logic control, GPS/INS, Kalman filtering, Urban navigation system",
author = "Nan Gao and Mengyuan Wang and Long Zhao",
note = "Publisher Copyright: {\textcopyright} 2016 TCCT.; 35th Chinese Control Conference, CCC 2016 ; Conference date: 27-07-2016 Through 29-07-2016",
year = "2016",
month = aug,
day = "26",
doi = "10.1109/ChiCC.2016.7554252",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "5732--5736",
editor = "Jie Chen and Qianchuan Zhao and Jie Chen",
booktitle = "Proceedings of the 35th Chinese Control Conference, CCC 2016",
address = "美国",
}