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Research on range-free location algorithm for wireless sensor network based on particle swarm optimization

机译:基于粒子群优化的无线传感器网络无距离定位算法研究

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摘要

Location technology is the key support technology of wireless sensor network (WSN). The hop number and hop distance information obtained by traditional distance vector hop (DV-Hop) location algorithm can only be acquired by solving the nonlinear equations, and the solution of the equation determines the accuracy of node location. Although the least squares method has better estimation performance, the solution results are sensitive to the average hop distance, which will lead to the large error in the solution of the equation. In order to solve the problem of location error caused by initial value sensitivity of least squares method in the coordinate calculation stage of unknown nodes and beacon nodes, a range-free location algorithm based on particle swarm optimization (PSO) is proposed in this paper. The proposed approach solves the problem of location error caused by initial value sensitivity of least squares method, obtains relatively accurate solution, and improves the accuracy of location algorithm. The experimental results show that the PSO algorithm has faster convergence speed and higher location accuracy than the non-optimization algorithm.
机译:位置技术是无线传感器网络(WSN)的关键支持技术。通过求解非线性方程,才能通过求解传统距离矢量跳(DV-Hop)位置算法而获得的跳数和跳距信息,并且等式的解决方案确定节点位置的准确性。尽管最小二乘方法具有更好的估计性能,但解​​决方案结果对平均跳距敏感,这将导致等式的解决方案中的误差。为了解决在未知节点和信标节点的坐标计算阶段中最小二乘法的初始值敏感性引起的位置误差问题,本文提出了一种基于粒子群优化(PSO)的无置位定位算法。所提出的方法解决了由最小二乘法的初始值灵敏度引起的位置误差的问题,获得相对准确的解决方案,并提高了位置算法的准确性。实验结果表明,PSO算法的收敛速度更快,更高的位置精度比非优化算法更高。

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