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Efficient Localization Algorithm for Wireless Sensor Networks Using Levenberg-Marquardt Refinement

机译:基于Levenberg-Marquardt改进的无线传感器网络高效定位算法

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摘要

Position location has recently been of great interest in wireless technologies due to its crucial role in many applications. In wireless sensor networks, the task of localizing sensor nodes with unknown position is important for the operation and configuration of the network. This significance has simulated research into variety of localization algorithms. In this paper we investigated the nonlinear localization problem with Levenberg-Marquardt (LM) algorithm based on time of arrival (ToA) measurements provided by the anchors. It is shown that the performance of proposed solution achieves significant accuracy and convergence. Cramer-Rao lower bound (CRLB) which is the lower bound on the variance for any localization algorithm is also derived for the proposed approach in the presence of additive Gaussian noise.
机译:由于位置定位在许多应用中都起着至关重要的作用,因此最近在无线技术中引起了极大的兴趣。在无线传感器网络中,对位置未知的传感器节点进行定位的任务对于网络的运行和配置很重要。这一意义已对各种定位算法进行了仿真研究。在本文中,我们根据锚提供的到达时间(ToA)测量值,使用Levenberg-Marquardt(LM)算法研究了非线性定位问题。结果表明,所提方案的性能达到了显着的精度和收敛性。在存在加性高斯噪声的情况下,对于所提出的方法,还推导了Cramer-Rao下界(CRLB),它是任何定位算法方差的下界。

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