Sensor fusion for target track maintenance with multiple UAVs based on Bayesian filtering method and hospitability map

Author(s):  
Zhijun Tang ◽  
O. Ozguner
2021 ◽  
pp. 1-10
Author(s):  
Lan Yu ◽  
Ning Peng

In the context of information education, English teaching needs to match the development of artificial intelligence to improve the intelligence of English teaching. Based on the artificial intelligence matching model, this paper constructs an English teaching reform model based on artificial intelligence algorithms. Moreover, based on the FISST multi-target tracking method, this paper firstly models the target state and measurement as RFS, and then uses the Bayesian filtering method to recursively calculate the target posterior PDF, which can estimate the number and state of targets in real time and make up for the shortcomings of traditional tracking methods. In addition, the system proposed in this article can be applied to online English teaching. Through this system, teachers can realize one-to-one matching of students, identify the status of students in time, and give corresponding English teaching methods to different students. Finally, this paper designs a controlled experiment to analyze the performance of the algorithm proposed in this paper. The research results show that the model constructed in this paper has certain practical effects.


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