室内定位中非视距的识别和抑制算法研究综述

A review of non-line-of-sight identification and mitigation algorithms for indoor localization

针对存在非视距(non-line-of-sight,NLOS)的室内定位算法进行研究.首先描述室内定位中的常用技术和算法(航迹推算、指纹识别定位、邻近探测、极点定位、三角定位、多边定位、质心定位),概括其原理、优缺点和适用场景;其次,通过仿真测试说明研究NLOS识别和抑制的必要性;再次,分别介绍NLOS识别和NLOS抑制的几类算法,NLOS识别算法包括统计学方法、几何关系法、机器学习法、信道特征提取法和虚点密度识别法,NLOS抑制算法包括模糊理论法、引入平衡参数法、几何关系法、小波去噪法、机器学习类算法、凸优化类算法、残差类算法、最小二乘类算法和多维缩放类算法;最后,对全文进行总结并指出NLOS室内定位亟待解决的问题.

The indoor localization algorithm with non-line-of-sight(NLOS) is studied.Firstly,we describe the techniques widely used in indoor localization and algorithms(dead reckoning,fingerprint identification,adjacent to detect,orientation of the pole,triangulation,multilateral,centroid localization),and summarize the principle,advantages,disadvantages and applicable scenario.Secondly,the necessity of studying NLOS identification and mitigation is illustrated by simulation test.Then,several algorithms of NLOS identification and mitigation are introduced respectively.NLOS identification algorithms include statistical methods,geometric relation methods,machine learning methods,channel feature extraction methods and virtual point density recognition methods.Moreover,NLOS mitigation algorithms include fuzzy theory methods,introduced equilibrium parameter methods,geometric relation methods,wavelet denoising methods,machine learning methods,convex optimization methods,residual methods,least square methods and multidimensional scaling methods.Finally,this paper summarizes the whole paper and points out the problems to be solved in NLOS indoor localization.