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A Drone Localization System Based on Multiple Time Delays Fusion

机译:基于多时延融合的无人机定位系统

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The recent years have witnessed the prosperity of the amateur drones. In spite of the great convenience brought by drones, the potential issues caused by drones, including public security and individual privacy leakage, cannot be overlooked. To counter the abuse of drones, in this paper, we design a novel drone localization system using two tetrahedral acoustic arrays, which can effectively localize drones within 100-meter range. We propose a novel time difference of arrival (TDOA) estimation algorithm which combines generalized crosscorrelation and probabilistic data association algorithms to accurately estimate TDOA. Different from the existing TDOA estimation algorithms, the proposed algorithm overcomes the multi-path effect and ensures the effectiveness under the low-signal-noise ratio environment. In order to further improve the performance of the proposed algorithm, we develop a novel algorithm to optimize the procedure of TDOA initialization based on dynamic programming. Finally, extensive experiments have been implemented to verify the effectiveness of our system and algorithms.
机译:近年来,目睹了业余无人机的繁荣。尽管无人机带来了极大的便利,但是由无人机引起的潜在问题,包括公共安全和个人隐私泄露,也不能忽视。为了解决无人机的滥用问题,在本文中,我们设计了一种使用两个四面体声学阵列的新型无人机定位系统,该系统可以有效地将无人机定位在100米范围内。我们提出了一种新颖的到达时间差(TDOA)估计算法,该算法将广义互相关和概率数据关联算法结合起来,可以准确地估计TDOA。与现有的TDOA估计算法不同,该算法克服了多径效应,确保了在低信噪比环境下的有效性。为了进一步提高所提出算法的性能,我们开发了一种新颖的算法来优化基于动态规划的TDOA初始化过程。最后,已经进行了广泛的实验,以验证我们的系统和算法的有效性。

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