@inproceedings{a57a917ba7354a22ac59676452c5b3ae,
title = "Optimal sequential estimation for multirate dynamic systems with unreliable measurements and correlated noise",
abstract = "In the field of target tracking and navigation, multi-sensor data fusion has been widely applied. Most of the data fusion algorithms are built on the premise that the sensor observation information is reliable. However, in practical problems, due to the limitation of communication and sensor fault, etc., data missing or unreliable measurements will happen inevitably. In addition, at present a lot of research is aimed at the situation where measurement noise between various sensors is not relevant, and process noise and measurement noise is irrelevant. Noise correlation is more practical. In this paper, a multi-rate multi-sensor data fusion state estimation algorithm with unreliable observations under correlated noises is presented. A numerical example is given to show the feasibility and effectiveness of the presented algorithm.",
keywords = "correlated noise, sequential fusion, state estimation, unreliable measurements",
author = "Liping Yan and Jun Liu and Lu Jiang and Yuanqing Xia and Bo Xiao and Yang Liu and Mengyin Fu",
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.2016.7554114",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "4900--4905",
editor = "Jie Chen and Qianchuan Zhao and Jie Chen",
booktitle = "Proceedings of the 35th Chinese Control Conference, CCC 2016",
address = "United States",
}