A Novel NLOS Mitigation Algorithm for UWB Localization in Harsh Indoor Environments

被引:278
作者
Yu, Kegen [1 ,2 ]
Wen, Kai [2 ]
Li, Yingbing [2 ]
Zhang, Shuai [2 ]
Zhang, Kefei [1 ,3 ]
机构
[1] China Univ Min & Technol, Sch Environm Sci & Spatial Informat, Xuzhou 221116, Jiangsu, Peoples R China
[2] Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430079, Hubei, Peoples R China
[3] RMIT Univ, Sch Sci, Satellite Positioning Atmosphere Climate & Enviro, Melbourne, Vic 3000, Australia
关键词
Fuzzy sets; least squares method; non-line-of-sight identification and mitigation; robustness; ultra-wideband; ERROR MITIGATION; LOCATION; CHANNEL; ACCURACY;
D O I
10.1109/TVT.2018.2883810
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Non-line-of-sight (NLOS) propagation of radio signals can significantly degrade the performance of ultra-wideband localization systems indoors, it is hence crucial to mitigate the NLOS effect to enhance the accuracy of positioning. The existing NLOS mitigation algorithms to improve localization accuracy are either by compensating range errors through NLOS identification and mitigation methods for ranging or by using dedicated localization techniques. However, they are only applicable to some specific scenarios due to some special assumptions or the need of a priori knowledge, such as thresholds and distribution functions. Another disadvantage is that they neither have the capability to evaluate the magnitude of NLOS effect nor take account of the residual NLOS range errors during location estimation. To remedy these problems, this paper proposes a less environment-dependent and a priori knowledge-independent NLOS identification and mitigation method for ranging which is able to determine the specific NLOS channel. Based on the identified channel information, a rule is developed to select appropriate NLOS ranges for location estimation. Meanwhile, an equality constrained Taylor series robust least squares (ECTSRLS) technique is proposed to suppress residual NLOS range errors by introducing robustness to Taylor series least squares method. All these constitute our FCE-ECTSRLS NLOS mitigation algorithm. The performance of the proposed algorithm is compared with four existing NLOS mitigation algorithms by both static and mobile localization experiments in a harsh indoor environment. Experimental results have demonstrated that the proposed FCE-ECTSRLS algorithm outperforms the other four algorithms significantly.
引用
收藏
页码:686 / 699
页数:14
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