基于DV-Hop定位算法的改进

针对DV-Hop算法采用跳数乘以平均每跳跳距估算节点间的跳距，利用三边测量法或极大似然估计法估算节点坐标信息，算法过程存在缺陷从而造成定位误差过高的问题。为此提出一种基于节点密度区域划分的DV-Hop改进算法（DZDV-Hop），依据网络的连通度和节点密度限制参与估算的信标节点的跳数，采用加权质心法估算定位坐标。Matlab仿真测试结果表明，在相同的网络硬件和拓扑结构环境下，改进后的算法能有效地减少节点通信量，且平均定位误差率比传统的DV-Hop算法减少了13.6%左右，提高了定位精度。

Improvement of DV-Hop based localization algorithm

DV-Hop algorithm uses the hop number multiplied by the average distance per hop to estimate the distance between nodes and the trilateral measurement or the maximum likelihood to estimate the node coordinate information, which has defects and then causing too many positioning errors. This paper presented an improved DV-Hop algorithm based on node density regional division (Density Zoning DV-Hop, DZDV-Hop), which used the connectivity of network and the node density to limit the hop number of the estimated node coordinate information and the weighted centroid method to estimate the positioning coordinates. Compared with the traditional DV-Hop algorithm in the same network hardware and topology environment, the result of Matlab simulation test shows that, the communication amount of nodes can be effectively reduced and the positioning error rate can be reduced by 13.6% by using the improved algorithm, which can improve the positioning accuracy.