中文摘要：

针对室内强噪声环境高精度、高顽健性定位问题，把顽健估计理论和变尺度法应用于室内定位，提出了基于顽健估计的室内节点定位算法。该算法依据余差大小，采用权值自适应调整机制，对有效测量数据进行保权处理，对可利用测量数据进行降权处理，对有害测量数据进行淘汰处理。采用具有2次收敛特性的变尺度法对目标代价函数进行最小优化，实现节点快速定位。实验表明，该算法具有良好定位精度和定位顽健性，明显优于未采用顽健估计的普通最小二乘定位算法。

英文摘要：

A novel indoor localization algorithm was presented, which employs robust estimator to identify and restrain ranging outliers or gross errors and uses DFP （davidon fletcher powell） method to majorize the global object function with a convergence within 2 steps. It first divides all the ranging measurements into three different domains （effective information, usable information and bad information） according to the corresponding residual errors, and then adopts different weighting scheme （maintaining, down-weighting, rejecting） through self-adaptation during iterative process. Extensive simulation results confirm that this proposed localization scheme outperforms remarkably traditional least squares （LS）, which do not employ outlier identification and restraint.