基于自适应粒子群的改进DV-Hop节点定位优化算法

Bingquan Chen, Xingfeng Guo, Yuanfeng Huang, M. Yang
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引用次数: 1

摘要

针对传统的DV-Hop节点定位算法采用最小二乘法计算节点坐标存在误差,而传统的粒子群优化(PSO)算法容易陷入局部最优解的问题。提出了一种改进的DV-Hop自适应粒子群算法。跳定位算法(APSO-DV-Hop)。首先,修改传统DV-Hop定位算法中的平均跳距;其次,采用改进的自适应粒子群算法(PSO)提高粒子群算法的局部搜索能力;最后,将两种改进算法相结合,提高算法的节点定位精度。实验仿真结果表明,在相同通信开销和硬件条件下,该算法具有较高的定位精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved DV-Hop Node location Optimization Algorithm Based on Adaptive Particle Swarm
Aiming at the problem that the traditional DV-Hop node positioning algorithm uses the least square method to calculate the node coordinates, there is an error, while the traditional particle swarm optimization (PSO) algorithm is easy to fall into the local optimal solution. This paper proposes an improved DV-Hop adaptive particle swarm optimization. Hop positioning algorithm (APSO-DV-Hop). First, modify the average hop distance in the traditional DV-Hop positioning algorithm; Secondly, the improved adaptive particle swarm (PSO) algorithm is used to improve the local search capability of the particle swarm algorithm; Finally, the two improved algorithms are combined to improve the node positioning accuracy of the algorithm. Experimental simulation results show that the proposed algorithm has higher positioning accuracy under the same communication overhead and hardware conditions.
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