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首页> 外文期刊>International journal of ad hoc and ubiquitous computing >Joint time synchronisation and localisation of multiple source nodes in wireless sensor networks
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Joint time synchronisation and localisation of multiple source nodes in wireless sensor networks

机译:无线传感器网络中多个源节点的联合时间同步和本地化

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摘要

Time synchronisation and localisation should be jointly conducted for time-based source location estimates in an asynchronous network. In this paper semidefinite programming (SDP), complexity-reduced SDP and linear least square (LLS) estimator are proposed for time synchronisation and localisation of multiple source nodes. The proposed algorithms provide joint estimates for the source locations and clock parameters and avoid the shortcoming of maximum likelihood (ML) estimator that requires an initial solution. Then, a location refinement (LR) technique is designed to improve the accuracy performance of the estimated parameters. The simulations show that the original SDP algorithm provides better accuracy performance than the complexity-reduced SDP. However, the complexity-reduced SDP runs faster than the original SDP. Although the complexity of LLS estimator is lowest among three proposed algorithms, the convex optimisation algorithms, including the original SDP and complexity-reduced SDP, have more robust performance compared with the LLS estimator.
机译:对于异步网络中基于时间的源位置估计,应该联合进行时间同步和本地化。本文提出了半定规划(SDP),降低复杂度的SDP和线性最小二乘(LLS)估计器,用于多个源节点的时间同步和本地化。所提出的算法为源位置和时钟参数提供联合估计,并避免了需要初始解决方案的最大似然(ML)估计器的缺点。然后,设计一种位置优化(LR)技术以提高估计参数的准确性。仿真表明,与降低复杂度的SDP相比,原始SDP算法具有更好的精度。但是,降低了复杂性的SDP的运行速度比原始SDP快。尽管在三种提出的算法中LLS估计器的复杂度最低,但与LLS估计器相比,包括原始SDP和降低了复杂度的SDP在内的凸优化算法具有更强健的性能。

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