A lot of key problems need to be studied and solved in the field of WSN,and node self-localization is one of them. In numerous localization algorithms,DV-hop is popular with discussion or referenced localization algorithm,but it takes the results of hops multiplied by network average jumps as the actual distance between the nodes, while the accuracy of calculating the average every hop distance,the character of network, the node density, topology structure,etc are major factors which influence the positioning accuracy of DV-Hop algorithm. We put forward an improved DV-Hop algorithm, area division based semi-auto DV-Hop localization algorithm (ADBSA DV-Hop). Several ideas were employed to improve DV-Hop, including semi-auto average size of per hop acquirement,area division, and sticking to border. ADBSA DV-Hop was simulated on MATLAB platform, to compare with DV-Hop. Experiment indictes that ADBSA DV-Hop performs better than DV-Hop,and competently meets the localization requirement of sticking to border.%在WSN领域中有很多亟待研究和解决的关键问题,节点的自我定位是其中之一.在众多定位算法中,DV-HOP是广受讨论或引用的定位算法,但该算法使用跳数乘以网络平均跳距来代替节点间的实际距离,而平均每跳距离的计算精确度与网络的性状、节点密度、拓扑结构等有很大关系,直接影响到DV-HOP算法的定位精度.针对DV-Hop算法这一缺陷,从半自动获取平均每跳距离、划分定位区域和对边缘区域采用坐标贴边三个角度,提出命名为ADBSA DV-Hop的改进的DV-HOP算法.在MATLAB平台上对ADBSA DV-Hop算法与DV-Hop算法进行了对比仿真实验,结果表明,ADBSA DV-Hop算法运行性能好于DV-Hop算法,尤其满足贴边定位情景的需要.
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