面向室外环境下无线发射器定位的无人机传感器路径优化

IF 3.6 3区 医学 Q2 NEUROSCIENCES Network Neuroscience Pub Date : 2023-08-18 DOI:10.3390/network3030016
G. Tran, Takuto Kamei, Shoma Tanaka
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引用次数: 0

摘要

利用未知发射源的定位方法对非法无线电波进行监测。使用地面传感器的定位方法在发射器和传感器之间的距离是非视距(NLoS)的环境下,定位精度会下降。因此,利用无人机(uav)作为传感器,确保视线(LoS)条件,提高定位精度的研究正在进行中。然而,由于无人机在天空中可以自由飞行,使得基于粒子群优化(PSO)的飞行路径优化难以实现高效、准确的定位。本文分别通过圆轨道和自由路径两种方法对无人机的飞行路径进行优化,以实现对未知辐射源的高效、准确的室外定位。数值结果表明,该方法改善了定位估计误差的性能。特别是,在误差累积分布函数(CDF)的第90个百分位处进行评估时,与传统固定传感器情况下的定位估计误差55.02 m相比,该方法在圆形轨道上的定位估计误差为28.59 m,在自由路径轨道上的定位估计误差为12.91 m。
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Route Optimization of Unmanned Aerial Vehicle Sensors for Localization of Wireless Emitters in Outdoor Environments
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.
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来源期刊
Network Neuroscience
Network Neuroscience NEUROSCIENCES-
CiteScore
6.40
自引率
6.40%
发文量
68
审稿时长
16 weeks
期刊最新文献
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