期刊
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
卷 7, 期 6, 页码 1489-1497出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JAS.2020.1003180
关键词
Air combat; cubic B-spline interpolation; data fusion; reinforcement learning
资金
- Major Projects for Science and Technology Innovation 2030 [2018AA0100800]
- Equipment Pre-research Foundation of Laboratory [61425040104]
- Joint Fund of China Electronics Technology for Equipment Preresearch [6141B 08231110a]
- Funding for Short Visit Program of Nanjing University of Aeronautics and Astronautics (NUAA) [190915DF03]
In order to improve detection system robustness and reliability, multi-sensors fusion is used in modern air combat. In this paper, a data fusion method based on reinforcement learning is developed for multi-sensors. Initially, the cubic B-spline interpolation is used to solve time alignment problems of multi-source data. Then, the reinforcement learning based data fusion (RLBDF) method is proposed to obtain the fusion results. With the case that the priori knowledge of target is obtained, the fusion accuracy reinforcement is realized by the error between fused value and actual value. Furthermore, the Fisher information is instead used as the reward if the priori knowledge is unable to be obtained. Simulations results verify that the developed method is feasible and effective for the multi-sensors data fusion in air combat.
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