Cooperative positioning of UAV internet of things based on optimization algorithm

被引:2
|
作者
Hu, Hao [1 ]
Chen, YuLin [2 ,3 ]
Peng, Bao [4 ]
Li, Zhenjun [5 ]
Wu, Qibao [6 ]
Lin, ZiRan [7 ]
Wang, Xiaolei [8 ]
机构
[1] Bingtuan Xingxin Vocat & Tech Coll, Urumqi 830023, Peoples R China
[2] South China Normal Univ, Guangdong Prov Key Lab Opt Informat Mat & Technol, South China Acad Adv Optoelect, Guangzhou 510006, Peoples R China
[3] South China Normal Univ, Inst Elect Paper Displays, South China Acad Adv Optoelect, Guangzhou 510006, Peoples R China
[4] Shenzhen Inst Informat Technol, Shenzhen 518172, Peoples R China
[5] Shenzhen Inst Technol, Shenzhen 518116, Peoples R China
[6] Guangdong Prov Engn Ctr China Made High Performan, Shenzhen 518172, Peoples R China
[7] Tongji Univ, Shanghai 200092, Peoples R China
[8] Shenzhen Polytech, Shenzhen 518055, Peoples R China
关键词
UAV positioning; Collaborative positioning; Three-dimensional positioning; Optimization algorithm; LOCALIZATION;
D O I
10.1007/s11276-022-03062-1
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Unmanned Aerial Vehicle (UAV) Internet of things have been widely used in military and civilian fields such as rescue, disaster relief, urban planning. Positioning service is the core technology for UAVs to perform various tasks. However, the UAV may be attacked by external conditions, resulting in its inability to obtain self-location information during mission. For the positioning problem of UAV signal interference, this paper proposes a cooperative positioning of UAV based on optimization algorithm. In order to solve the difficulty of UAV positioning, we propose the following solutions. Firstly, we construct different numbers of beacon nodes by using the flight information of UAVs in different cycles. Secondly, the unknown number of the positioning to be solved of the UAV is reduced to improve the accuracy and speed of the subsequent optimization algorithm. Thirdly, A multi-objective optimization model is established of the UAV motion parameters under inequality constraints. And we utilize a penalty function to convert the optimization model into a minimal value solution problem under no constraints. Finally, the positioning results of each UAV are obtained by the optimization algorithm.
引用
收藏
页码:4495 / 4505
页数:11
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