融合跳数修正与动态布谷鸟搜索的改进DV⁃Hop算法  

Improved DV⁃Hop algorithm fusing hop correction and dynamic Cuckoo search

作　　者：任克强[1] 温晓珍 REN Keqiang;WEN Xiaozhen(School of Information Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China)

机构地区：[1]江西理工大学信息工程学院,江西赣州341000

出　　处：《现代电子技术》2021年第5期21-26,共6页Modern Electronics Technique

基　　金：国家自然科学基金资助项目(61562038)。

摘　　要：针对DV⁃Hop算法定位精度低的问题,提出一种跳数量化与布谷鸟搜索优化相结合的改进DV⁃Hop算法。改进算法首先利用修正因子对节点间的跳数进行修正,以减小由最小跳数不准确所引起的累积误差;然后将网络中节点的通信区域划分为3个互不相交的子区域,并利用几何方法修正跳距;最后引入能动态调整搜索步长的混合布谷鸟搜索算法,代替极大似然估计法计算节点坐标,进一步优化定位效果。实验结果表明,在不影响硬件成本的前提下,相比于DV⁃Hop算法和Cuckoo Search DV⁃Hop算法,改进算法的平均定位误差有明显下降,节点定位精度更佳。An improved DV⁃Hop algorithm combining hop count quantization and Cuckoo search optimization is proposed against the low positioning accuracy of the DV⁃Hop algorithm.In the improved algorithm,the hop count between the nodes are corrected by the correction factors to reduce the accumulative error caused by the inaccuracy of the minimum hop count.And then,the communication area of the nodes in the network is divided into 3 subareas that are mutually disjoint.In addition,the hop distance is corrected with a geometric approach.Finally,a hybrid Cuckoo search algorithm that can dynamically adjust the step size in search is introduced to replace the maximum likelihood estimation for calculation of the node coordinates,so as to further optimize the positioning effect.Experimental results show that,on the premise of no effect on the hardware cost,the average positioning error of the improved algorithm is declined more significantly,and its positioning accuracy is much better in comparison with both the DV⁃Hop algorithm and the Cuckoo search DV⁃Hop algorithm.

关 键 词：改进DV⁃Hop算法 跳数修正 跳距修正 布谷鸟搜索 无线传感器网络 节点定位 

分 类 号：TN711.1-34[电子电信—电路与系统] TP393[自动化与计算机技术—计算机应用技术]