Route Optimization of Unmanned Aerial Vehicle Sensors for Localization of Wireless Emitters in Outdoor Environments

被引:0
|
作者
Tran, Gia Khanh [1 ]
Kamei, Takuto [1 ]
Tanaka, Shoma [2 ]
机构
[1] Tokyo Inst Technol, Tokyo 1528550, Japan
[2] Softbank Corp, Tokyo 1057537, Japan
来源
NETWORK | 2023年 / 3卷 / 03期
关键词
RF fingerprint; localization; UAV; route optimization; PSO; ALGORITHMS;
D O I
10.3390/network3030016
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Localization methods of unknown emitters are used for the monitoring of illegal radio waves. The localization methods using ground-based sensors suffer from a degradation of localization accuracy in environments where the distance between the emitter and the sensor is non-line-of-sight (NLoS). Therefore, research is being conducted to improve localization accuracy by utilizing Unmanned Aerial Vehicles (UAVs) as sensors to ensure a line-of-sight (LoS) condition. However, UAVs can fly freely over the sky, making it difficult to optimize flight paths based on particle swarm optimization (PSO) for efficient and accurate localization. This paper examines the optimization of UAV flight paths to achieve highly efficient and accurate outdoor localization of unknown emitters via two approaches, a circular orbit and free-path trajectory, respectively. Our numerical results reveal the improved localization estimation error performance of our proposed approach. Particularly, when evaluating at the 90th percentile of the error's cumulative distribution function (CDF), the proposed approach can reach an error of 28.59 m with a circular orbit and 12.91 m with a free-path orbit, as compared to the conventional fixed sensor case whose localization estimation error is 55.02 m.
引用
收藏
页码:326 / 342
页数:17
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