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Robust and Cooperative Localization for Underwater Sensor Networks in the Existence of Malicious Anchors

机译:存在恶意锚点的水下传感器网络的鲁棒合作定位

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摘要

Precise and robust localization in three-dimensional underwater sensor networks is still an important research problem. This problem is particularly challenging if there are some malicious anchors among ordinary anchor nodes that will broadcast their locations falsely and deliberately. In this paper, we study how to self-localize large teams of underwater sensor nodes under the condition that some malicious anchor nodes mixed with ordinary anchors. Due to malicious characteristic of some deliberate anchor nodes, an iterative and cooperative 3D-localization algorithm for underwater sensor networks in the existence of malicious anchors is proposed in this paper. The proposed robust localization algorithm takes advantage of distributed reputation voting method within 1-Hop neighboring reference nodes to detect and eliminate malicious anchor nodes. Moreover, one kind of Minimum Mean Squared Error estimation based iterative localization method is applied to determine accurate location information. Additionally, we analyze and prove that our localization algorithm would have a bounded error when the number of malicious anchors is smaller than a certain threshold. Extensive simulation results are provided to demonstrate performance improvements comparing to traditional Minimum Mean Squared Error and Attack Resistant Minimum Mean Squared Error based localization methods in terms of localization accuracy and coverage ratio.
机译:三维水下传感器网络中精确,鲁棒的定位仍然是一个重要的研究问题。如果普通锚点节点之间存在一些恶意锚点,这些错误锚点将以虚假和故意的方式传播其位置,则此问题尤其具有挑战性。在本文中,我们研究了在一些恶意锚节点与普通锚混合的情况下如何对大型水下传感器节点团队进行自定位。针对某些故意锚节点的恶意特征,提出了在存在恶意锚的情况下水下传感器网络的迭代协作3D定位算法。所提出的鲁棒定位算法利用1-Hop相邻参考节点中的分布式信誉投票方法来检测和消除恶意锚节点。此外,一种基于最小均方误差估计的迭代定位方法被用于确定准确的位置信息。此外,我们分析并证明,当恶意锚点的数量小于某个阈值时,我们的定位算法会出现有界错误。提供了大量的仿真结果,以证明与传统的基于最小均方误差和基于抗攻击性最小均方误差的定位方法相比,在定位精度和覆盖率方面的性能提高。

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