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Optimal Cooperative Sensing using a Team of UAVs

机译:使用无人机团队的最佳合作感测

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The authors investigates the joint optimal estimation of both the position and velocity of a ground moving target (GMT) using pulse Doppler radars on-board unmanned aerial vehicles (UAVs). The problem of cooperative estimation using a UAV team and the optimization of the team's configuration to achieve optimal GMT position and velocity estimates are addressed. Based on the Cramer-Rao bound, the minimum achievable error variance of the GMT position and velocity estimates is derived. The expression of the minimum achievable estimation error variance for unbiased estimation provided by the Cramer-Rao bound is minimized yielding the optimal configuration of the UAV team. Our solution is complete in that it addresses various GMT tracking scenarios and an arbitrary number of UAVs. Optimal sensor geometries for typical applications are illustrated
机译:作者研究了使用脉冲多普勒雷达在无人机上对地面移动目标(GMT)的位置和速度进行联合最优估计的方法。解决了使用无人机团队进行协同估算以及优化团队配置以实现最佳GMT位置和速度估算的问题。基于Cramer-Rao边界,得出GMT位置和速度估计值的最小可实现误差方差。由Cramer-Rao边界提供的无偏估计的最小可实现估计误差方差的表达式被最小化,从而产生了无人机团队的最佳配置。我们的解决方案是完整的,因为它可以解决各种GMT跟踪方案和任意数量的无人机。说明了典型应用的最佳传感器几何形状

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