@inproceedings{72ccb8f3bdf94c4195554b285809bae7,
title = "An Overall Weighted Fusion Algorithm Based on Dynamic Optimal Estimation",
abstract = "Based on the background of cooperative detection of target by multiple UAVs, this paper proposes an efficient multi-sensor data fusion algorithm, which is called the overall weighted fusion algorithm based on dynamic optimal estimation (abbreviated as DOE-OWFA) Based on the weighted fusion by the least squares method, the algorithm makes full use of the state estimation property of Kalman Alter for data processing and state estimation. In order to evaluate the performance of the algorithm, we conducted simulation tests with the help of MATLAB. The simulation results show that the algorithm proposed in this paper has higher fusion accuracy and better robustness compared with the same type of algorithms.",
keywords = "Data fusion, Kalman filter, Least squares",
author = "Zehu Wang and Guanglin He and Yukuan Liu",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Control, Electronics and Computer Technology, ICCECT 2023 ; Conference date: 28-04-2023 Through 30-04-2023",
year = "2023",
doi = "10.1109/ICCECT57938.2023.10140302",
language = "English",
series = "2023 IEEE International Conference on Control, Electronics and Computer Technology, ICCECT 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "750--754",
booktitle = "2023 IEEE International Conference on Control, Electronics and Computer Technology, ICCECT 2023",
address = "United States",
}