中文摘要：

基于测距的定位方法是无线传感器网络节点定位中一种常见的方法。测距定位方法往往将定位过程转化为数学优化问题。介绍了实现测距定位下的LS-SDR与SAL-SDR两种半定规划定位算法,并同时介绍了LS-LM、SLS-LM、SLS-US与SLS-S等4种定位算法。仿真实验分析和比较了6种不同定位算法的平均RMS定位误差,结果表明相对于其他4种定位算法,LS-SDR和LS-LM算法的定位误差较小。在信标节点数量较少的情况下,LS-LM算法的定位结果有可能发生奇异,造成定位结果的严重失真。而LS-SDR算法对于奇异的发生具有较好的抵抗能力,此时LS-SDR算法的平均RMS定位误差将优于LS-LM算法。

英文摘要：

Range-based localization is a familiar method of node localization for wireless sensor networks. Range- based localization often transforms the process of localization to mathematical optimization problem. This paper introduces two different localization algorithms of LS-SDR and SAL-SDR to realize the range-based localization with semidefinite optimization and also represents other four localization algorithms of LS-LM, SLS-LM, SLS-US and SLS-S. Simulation experiments analyze and compare the mean RMS errors with six different localization algorithms. The results also show the located errors of LS-LM or LS-SDR algorithm are less than those of other four localization algorithms. When the number of anchors is small, LS-LM algorithm is possible to produce singular localization results. However the algorithm of LS-SDR has the capability of resisting the singularity, so the mean RMS error of LS-SDR will be better than that of LS-LM.