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A new approach for Simultaneous Localization of UAV and RF Sources (SLUS)

机译:同时定位无人机和射频源(SLUS)的新方法

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In this paper, a new approach for Simultaneous Localization of UAV and RF Sources (SLUS) is proposed. In the UAV-based localization of RF sources, such as a cell phone in a search and rescue mission, the UAV navigation errors are a significant source of localization error. Although the use of GPS can reduce UAV localization error significantly resulting in more accurate RF source localization, however, if the GPS is not available temporarily or permanently, the accuracy of UAV-based localization decreases rapidly. The proposed approach solves these two connected problems, i.e. UAV localization and RF source localization, simultaneously to decrease the error of UAV position estimation and the error of RF sources localization. The prediction of UAV pose is done in parallel to RF source position prediction first. Then the predicted states are augmented and the augmented predicted state information is corrected in SLUS using the range and bearing observations. The simulation results show that this method can reduce RF source's position estimation error and prevent the divergence of UAV navigation in latitude and longitude channels. In the other words, the RF features available in the environment can be used to improve the UAV navigation.
机译:本文提出了一种同时定位无人机和射频源(SLUS)的新方法。在基于RF的基于UAV的定位中,例如在执行搜救任务的手机中,UAV导航错误是导致定位错误的重要原因。尽管使用GPS可以大大减少UAV定位误差,从而导致更精确的RF源定位,但是,如果GPS暂时或永久不可用,基于UAV的定位精度将迅速下降。所提出的方法解决了这两个相关的问题,即UAV定位和RF源定位,同时减小了UAV位置估计的误差和RF源定位的误差。 UAV姿态的预测首先与RF源位置预测并行进行。然后,使用范围和方位观测值对预测状态进行增强,并在SLUS中对增强的预测状态信息进行校正。仿真结果表明,该方法可以减少射频源的位置估计误差,防止无人机导航在经纬度通道上出现发散。换句话说,环境中可用的RF功能可用于改善无人机导航。

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