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Localization under anchor node uncertainty for underwater acoustic sensor networks

机译:水下声传感器网络在锚节点不确定性下的定位

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摘要

This paper deals with the problem of sensor node localization in the presence of uncertainty in anchor node location. Aqueous environments are prone to adverse effects of underwater currents. This adversity causes non-negligible mobility to the anchor nodes deployed under water. Localization in the presence of uncertainty in the anchor node location is quite challenging. Also, the authors consider the ray-bending property of underwater medium due to depth dependent sound speed, to furnish the accurate position estimate of the target node. Standard ray equations are used to model the path followed by acoustic rays in water. Maximum likelihood estimation is proposed to estimate the location of target node with uncertainty in anchor node positions and is compared with the scheme with exact knowledge of anchor node positions, and the results are reported. Monte Carlo simulation is used to assess the performance of the proposed method. Also, the Cramer-Rao lower bound with uncertainty in anchor nodes is derived and described. Simulation results of the proposed algorithm outperform the existing algorithm with known anchor location by up to 49.4%, and hence, accuracy is improved in the proposed method.
机译:在锚节点位置不确定的情况下,本文解决了传感器节点定位问题。水性环境容易受到水下水流的不利影响。这种逆境导致了在水下部署的锚节点的流动性不可忽略。在锚节点位置存在不确定性的情况下进行定位非常具有挑战性。同样,作者考虑了由于深度依赖声速而引起的水下介质的射线弯曲特性,以提供目标节点的准确位置估计。标准射线方程式用于模拟水中声波所遵循的路径。提出了最大似然估计来估计目标节点在锚节点位置中具有不确定性的位置,并将其与具有锚节点位置确切知识的方案进行比较,并报告结果。蒙特卡洛模拟用于评估所提出方法的性能。此外,推导并描述了锚节点中具有不确定性的Cramer-Rao下界。所提算法的仿真结果比已知锚点位置的现有算法高出49.4%,从而提高了算法的准确性。

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