An Overall Weighted Fusion Algorithm Based on Dynamic Optimal Estimation

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 le...

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Bibliographic Details
Published in2023 IEEE International Conference on Control, Electronics and Computer Technology (ICCECT) pp. 750 - 754
Main Authors Wang, Zehu, He, Guanglin, Liu, Yukuan
Format Conference Proceeding
LanguageEnglish
Published IEEE 28.04.2023
Subjects
Data fusion
Data integration
Filtering algorithms
Heuristic algorithms
Kalman filter
Kalman filters
Least squares
Robustness
Simulation
State estimation
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Summary: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.
DOI:10.1109/ICCECT57938.2023.10140302