基于分布式多跳误差估计目标位置感知算法

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％.%In order to improve the accuracy of the positioning system on the target location,and reduce excessive investment in hardware and energy costs,an energy efficiency target position aware algorithm(NFDV-Hop) is proposed.The positioning accuracy,DV-Hop algorithm uses the average distance per hop to estimate the distance between anchor nodes and unknown nodes,resulting in an estimated distance and the true distance is large error.The average jump size NFDV-Hop algorithm uses anchor nodes and the average number of hops between nodes anchors the distance,to determine position coordinates of the unknown node,and obtain the coordinates of the position after the introduction of the ratio of the estimated value to reduce the positioning error.The energy optimization,DV-Hop algorithm requires to repeatedly broadcast the node information,and the anchor node NFDV-Hop algorithm uses with a single position coordinate information itself to other nodes broadcast,thus greatly reducing the energy consumption of the node.Simulation results show that,compared DV-Hop algorithm based on least squares method and the improved particle swarm optimization based on DV-Hop algorithm,positioning accuracy NFDV-Hop localization algorithm is increased by 12.1％ and 9％.