Procapra Przewalskii Tracking Autonomous Unmanned Aerial Vehicle Based on Improved Long and Short-Term Memory Kalman Filters

NWIPB OpenIR

	Procapra Przewalskii Tracking Autonomous Unmanned Aerial Vehicle Based on Improved Long and Short-Term Memory Kalman Filters
	Luo, Wei; Zhao, Yongxiang; Shao, Quanqin; Li, Xiaoliang; Wang, Dongliang; Zhang, Tongzuo; Liu, Fei; Duan, Longfang; He, Yuejun; Wang, Yancang; Zhang, Guoqing; Wang, Xinghui; Yu, Zhongde
	2023
发表期刊	SENSORS
卷号	23 期号:8
摘要	This paper presents an autonomous unmanned-aerial-vehicle (UAV) tracking system based on an improved long and short-term memory (LSTM) Kalman filter (KF) model. The system can estimate the three-dimensional (3D) attitude and precisely track the target object without manual intervention. Specifically, the YOLOX algorithm is employed to track and recognize the target object, which is then combined with the improved KF model for precise tracking and recognition. In the LSTM-KF model, three different LSTM networks (f, Q, and R) are adopted to model a nonlinear transfer function to enable the model to learn rich and dynamic Kalman components from the data. The experimental results disclose that the improved LSTM-KF model exhibits higher recognition accuracy than the standard LSTM and the independent KF model. It verifies the robustness, effectiveness, and reliability of the autonomous UAV tracking system based on the improved LSTM-KF model in object recognition and tracking and 3D attitude estimation.
收录类别	SCIE
文献类型	期刊论文
条目标识符	http://210.75.249.4/handle/363003/61665
专题	中国科学院西北高原生物研究所
推荐引用方式 GB/T 7714	Luo, Wei,Zhao, Yongxiang,Shao, Quanqin,et al. Procapra Przewalskii Tracking Autonomous Unmanned Aerial Vehicle Based on Improved Long and Short-Term Memory Kalman Filters[J]. SENSORS,2023,23(8).
APA	Luo, Wei.,Zhao, Yongxiang.,Shao, Quanqin.,Li, Xiaoliang.,Wang, Dongliang.,...&Yu, Zhongde.(2023).Procapra Przewalskii Tracking Autonomous Unmanned Aerial Vehicle Based on Improved Long and Short-Term Memory Kalman Filters.SENSORS,23(8).
MLA	Luo, Wei,et al."Procapra Przewalskii Tracking Autonomous Unmanned Aerial Vehicle Based on Improved Long and Short-Term Memory Kalman Filters".SENSORS 23.8(2023).