中文摘要：

针对无线传感器网络的较大测距误差严重影响定位算法精度和鲁棒性的问题，利用节点均匀部署网络的拓扑特征，提出了一种基于局部网络拓扑特征的鲁棒节点定位算法（LFLS算法）。该算法通过构建节点测距高估粗差阈值参数和测距低估粗差阈值参数，在对未知节点1跳测距数据集进行粗差识别及剔除等预处理滤波的基础上，使用高斯加权最小二乘定位算法实现节点定位。仿真结果表明，基于局部网络拓扑特征的鲁棒节点定位算法的定位精度明显优于未采用局部网络拓扑特征进行粗差预处理的加权最小二乘定位算法，其中粗差测距直接相关节点的定位精度改进尤为明显。

英文摘要：

This paper presents a robust localization algorithm which employs local networks feature to identify and discard ranging outliers in evenly deployed sensor networks. It first filters out 1-hop ranging outliers of the unknown nodes by using the threshold parameters of extreme ranging overestimates and extreme ranging underestimate, and then employs Gausskernel-weighted least squares to position nodes. For received signal strength based range measurements, the simulation results confirm that this localization scheme outperforms the traditional weighted least squares （WLS）, which do not employ outlier identification and deletion. Especially, the scheme can remarkably improve the localization accuracy of the unknown nodes which are directly related to the outliers.