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首页> 外文期刊>Arabian Journal for Science and Engineering >Single- and Multi-UAV Trajectory Control in RF Source Localization
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Single- and Multi-UAV Trajectory Control in RF Source Localization

机译：射频源定位中的单UAV和多UAV轨迹控制

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摘要

In this paper, two trajectory control approaches are presented for any number of unmanned aerial vehicles (UAVs) in radio frequency (RF) source localization. The UAVs observe the received signal strength (RSS) in distinctive time intervals to localize a stationary RF source. The location of the source is estimated recursively applying the extended Kalman filter. The objective of the optimal trajectory control is to steer the UAVs to the locations which minimize the uncertainty about the target state. The Fisher information matrix (FIM) is inversely proportional to the estimation variance. Since the true target state is unknown, the FIM is approximated by the estimated target state. Two criteria based on the approximated FIM are applied to measure the information content of the observations to optimize the UAV waypoints: The D-optimality and the A-optimality. The objective of the present paper is to propose two trajectory control approaches for any number of UAVs in RSS-based localization to increase the target localization accuracy. The superiority of the trajectory optimization approach based on the D-optimality in terms of mean squared error is illustrated through simulation examples.
机译：在本文中，针对射频（RF）源定位中的任意数量的无人机（UAV），提出了两种轨迹控制方法。 UAV在不同的时间间隔内观察接收信号强度（RSS），以定位固定的RF源。使用扩展的卡尔曼滤波器递归地估计源的位置。最佳轨迹控制的目的是将无人机引导到使目标状态不确定性最小的位置。 Fisher信息矩阵（FIM）与估计方差成反比。由于真实的目标状态未知，因此FIM由估算的目标状态近似。基于近似FIM的两个标准用于测量观测的信息内容以优化无人机航路点：D最优性和A最优性。本文的目的是为基于RSS的定位中的任意数量的无人机提出两种轨迹控制方法，以提高目标定位精度。通过仿真实例说明了基于D最优性的轨迹优化方法在均方误差方面的优越性。

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