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http://dx.doi.org/10.11003/JPNT.2017.6.3.105

Performance Analysis of the Wireless Localization Algorithms Using the IR-UWB Nodes with Non-Calibration Errors  

Cho, Seong Yun (Department of Robot Engineering, Kyungil University)
Kang, Dongyeop (Daegu-Gyeongbuk Research Center, Electronic and Telecommunications Research Institute)
Kim, Jinhong (Daegu-Gyeongbuk Research Center, Electronic and Telecommunications Research Institute)
Lee, Young Jae (Daegu-Gyeongbuk Research Center, Electronic and Telecommunications Research Institute)
Moon, Ki Young (Daegu-Gyeongbuk Research Center, Electronic and Telecommunications Research Institute)
Publication Information
Journal of Positioning, Navigation, and Timing / v.6, no.3, 2017 , pp. 105-116 More about this Journal
Abstract
Several wireless localization algorithms are evaluated for the IR-UWB-based indoor location with the assumption that the ranging measurements contain the channelwise Non-Calibration Error (NCE). The localization algorithms can be divided into the Model-free Localization (MfL) methods and Model-based Kalman Filtering (MbKF). The algorithms covered in this paper include Iterative Least Squares (ILS), Direct Solution (DS), Difference of Squared Ranging Measurements (DSRM), and ILS-Common (ILS-C) methods for the MfL methods, and Extended Kalman Filter (EKF), EKF-Each Channel (EKF-EC), EKF-C, Cubature Kalman Filter (CKF), and CKF-C for the MbKF. Experimental results show that the DSRM method has better accuracy than the other MfL methods. Also, it demands smallest computation time. On the other hand, the EKF-C and CKF-C require some more computation time than the DSRM method. The accuracy of the EKF-C and CKF-C is, however, best among the 9 methods. When comparing the EKF-C and CKF-C, the CKF-C can be easily used. Finally, it is concluded that the CKF-C can be widely used because of its ease of use as well as it accuracy.
Keywords
IR-UWB; non-calibration error; model-free localization; model-based Kalman filtering; common bias;
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