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	Unsupervised Feature Fusion Combined with Neural Network Applied to UAV Attitude Estimation
	Dai Xin; Yimin Zhou; Meng Shan; Qingtian Wu
	2018
会议日期	2018
会议地点	Kuala Lumpur, Malaysia
英文摘要	In the field of an unmanned aerial vehicle (UAV), the navigation algorithm with high precision and easy implementation is a hot topic of research, and the key of UAV control is to obtain accurate and real-time attitude information. In this paper, a feature fusion algorithm based on unsupervised deep autoencoder (DAE) is proposed. It is used for data fusion of multiple sensors. The experimental results show that the unsupervised feature fusion algorithm can effectively improve the accuracy and has the potential to be applied to the data fusion of UAV sensors
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/13852]
专题	深圳先进技术研究院_集成所
推荐引用方式 GB/T 7714	Dai Xin,Yimin Zhou,Meng Shan,et al. Unsupervised Feature Fusion Combined with Neural Network Applied to UAV Attitude Estimation[C]. 见:. Kuala Lumpur, Malaysia. 2018.

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