中文摘要：

为了充分利用锚节点之间的信息以及提高基于跳数的定位算法精度,提出基于线性回归的两种算法LRDH（Linear Regression DV-HOP）和MMLR（Min and Max Linear Regression）.该算法利用线性回归分析的方法,对锚节之间跳数和距离信息建立线性回归模型来计算未知节点与锚节点之间的距离,并将计算结果运用到全网的定位中.仿真结果表明,LRDH算法和MMLR算法定位精度都优于DV-HOP算法,特别是MMLR算法比DV-HOP算法定位精度有大幅的提高.

英文摘要：

In order to make full use of the information among wireless sensor nodes,and improve the accuracy of the hop-based localization algorithm,two localization algorithms based on the linear regression method LRDH（Linear Regression DV-HOP） and MMLR（Min and Max Linear Regression） are proposed in this paper. Using the regression model,the new algorithms make regression analysis the information of hops and distance to estimate the distance between unknown and anchor nodes. Then this distance values are used to locate the unknown nodes. Through extensive simulation,the results show that the position errors of LRDH and MMLR algorithm are fewer than DV-HOP,especially the MMLR has good performance.