使用协作无人机机群对间歇性射频源进行集员定位
Set-membership localization of intermittent RF sources using a fleet of collaborating UAVs
AI总结：
本文提出集员方法（SMA）用于协作无人机机群定位间歇性射频源，仿真显示其在定位精度和收敛速度上优于贝叶斯基线方法。
AI中文摘要：
本文提出了一种集员方法（SMA），用于定位由协作无人机（UAV）机群观测到的射频（RF）源。考虑到具有间歇性和周期性发射模式的频率可分离射频发射器，SMA评估源位置集合估计值及无源集合。仿真结果表明，SMA在定位精度和收敛速度方面优于贝叶斯基线方法。
英文摘要：
This paper proposes a set-membership approach (SMA) to localize radio frequency (RF) sources observed by a collaborating fleet of Unmanned Aerial Vehicles (UAVs). Considering frequency-separable RF transmitters with intermittent and periodic emission patterns, %and unknown but bounded periods the SMA evaluates set estimates of the source locations and a set free of sources. Simulation results show that SMA outperforms a Bayesian baseline approach in terms of localization accuracy and convergence speed.
