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

Abstract

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.