基于分布式多跳误差估计目标位置感知算法

发布时间：2018-07-09 11:50

本文选题：分布式多跳误差估计 + 位置锁定　；参考：《电子技术应用》2017年11期

【摘要】：为了提高定位系统在目标定位上的精度,减少过多的硬件设施投入和能量成本,提出分布式多跳误差估计的能量高效目标位置感知算法(NFDV-Hop)。在定位精度上,DV-Hop算法采用每跳的平均距离来估计锚节点和未知节点之间的距离,导致估计距离与真实距离存在较大误差,而NFDV-Hop算法使用锚节点的平均跳数的大小以及锚节点间的平均跳距离,求得未知节点的位置坐标,并在得到坐标估计值后引入位置比值来减少定位误差。在能量优化上,DV-Hop算法需向节点多次广播信息,而NFDV-Hop算法所采用的锚节点只需向其他节点广播一次自身的位置坐标信息,从而大大减少节点的能量消耗。仿真结果表明,相比基于最小二乘法的DV-Hop算法以及基于改进粒子群优化的DV-Hop算法,NFDV-Hop定位算法的定位精度分别提高了12.1%和9%。
[Abstract]:In order to improve the accuracy of the positioning system and reduce the excessive hardware and energy cost, a distributed multi-hop error estimation based on energy-efficient target location sensing algorithm (NFDV-Hop) is proposed. The DV-Hop algorithm uses the average distance per hop to estimate the distance between the anchor node and the unknown node, which leads to a large error between the estimated distance and the real distance. The NFDV-Hop algorithm uses the average number of hops of anchor nodes and the average hopping distance between anchor nodes to obtain the position coordinates of unknown nodes. In energy optimization, the DV-Hop algorithm needs to broadcast information to nodes many times, while the anchor node used in NFDV-Hop algorithm only needs to broadcast its position coordinate information to other nodes once, thus greatly reducing the energy consumption of nodes. Simulation results show that compared with DV-Hop algorithm based on least square method and DV-Hop algorithm based on improved particle swarm optimization, the localization accuracy of NFDV-Hop algorithm is improved by 12. 1% and 9% respectively.
【作者单位】：四川职业技术学院电子电气工程系;湖南科技学院电子与信息工程学院;
【基金】：湖南省科技计划项目(2014FJ6095)
【分类号】：TN929.5;TP212.9

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