@inproceedings{f42dd5e0c3b64e5ba21ee5f27afec46c,
title = "Research on MAV indoor localization and yaw estimation algorithm based on onboard ultrasonic sensors",
abstract = "Because of the lack of GPS signal and strong magnetic field interference in indoor environment, the indoor localization of micro aerial vehicle(MAV)is a challenging problem in practice. In this paper, an MAV indoor positioning algorithm is proposed, which does not rely on magnetic compass and GPS. The improved unscented Kalman filter (UKF) algorithm is used to fuse the information only four ultrasonic sensors and the Inertial Measurement Unit carried by the drone itself to localize in the indoor environment with a prior map. This method does not rely on magnetic compass, so it greatly reduces the impact of indoor electromagnetic environment on localization. Results from simulation demonstrates the effectiveness of the proposed algorithm.",
keywords = "IMU, Indoor localization, MAV, Prior map, UKF, Ultrasonic sensors",
author = "Xiaoke Feng and Lingyu Yang and Jing Zhang and Yuhan Mou",
note = "Publisher Copyright: {\textcopyright} 2019 Technical Committee on Control Theory, Chinese Association of Automation.; 38th Chinese Control Conference, CCC 2019 ; Conference date: 27-07-2019 Through 30-07-2019",
year = "2019",
month = jul,
doi = "10.23919/ChiCC.2019.8866643",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "4147--4154",
editor = "Minyue Fu and Jian Sun",
booktitle = "Proceedings of the 38th Chinese Control Conference, CCC 2019",
address = "美国",
}