@inproceedings{91302d8d97584e51ae234c37e13df870,
title = "Spatial alignment method based on cooperative multi-sensors target detection",
abstract = "This paper is focused on the estimation for the multi-sensors alignment errors. There are two types of biases being discussed: sensor measurement (systemic) biases and attitude biases. An improved ECEF-KF algorithm is proposed for the estimation of 12-D error vector. Firstly, we develop the state models of fixed systemic biases and slowly time-varying attitude errors. Secondly, the measurements to public target are transformed from body frames into ECEF coordinate system, isolating the motion and rotation of platforms. Thirdly, a Kalman Filter based on linear pseudo-measured function is used to estimate the error state. Simulations demonstrate that the alignment errors can be exactly estimated and the accuracy of target tracking can be dramatically improved by error compensation.",
keywords = "Kalman filter, alignment, error compensation, sensor, target detection",
author = "Lu Xiaodong and Xie Yuting and Zhou Jun",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 3rd International Conference on Control and Robotics Engineering, ICCRE 2018 ; Conference date: 20-04-2018 Through 23-04-2018",
year = "2018",
month = jun,
day = "8",
doi = "10.1109/ICCRE.2018.8376473",
language = "英语",
series = "2018 3rd International Conference on Control and Robotics Engineering, ICCRE 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "243--248",
booktitle = "2018 3rd International Conference on Control and Robotics Engineering, ICCRE 2018",
}