Robust Localization Based on ML-Type, Multi-Stage ML-Type, and Extrapolated Single Propagation UKF Methods under Mixed LOS/NLOS Conditions
- Title
- Robust Localization Based on ML-Type, Multi-Stage ML-Type, and Extrapolated Single Propagation UKF Methods under Mixed LOS/NLOS Conditions
- Author
- 박치현
- Keywords
- Localization; Robust; maximum likelihoodtype estimator (M estimator); multi-stage maximum likelihoodtype estimator (MM estimator); extrapolated single propagation unscented Kalman filter; weighted least squares
- Issue Date
- 2020-09
- Publisher
- Institute of Electrical and Electronics Engineers
- Citation
- IEEE Transactions on Wireless Communications, v. 19, no. 9, page. 5819-5832
- Abstract
- This paper presents robust localization algorithms that use range measurements to estimate the location parameters. The non-line-of-sight (NLOS) propagation of a signal can severely deteriorate the estimation performance in indoor and population-dense urban areas. Therefore, the robust localization algorithms are considered in this paper. In particular, the robust statistics-based localization is dealt with. The maximum likelihood (ML)-type and multi-stage ML-type method-based weighted least squares (WLS) algorithms and robust extrapolated single propagation unscented Kalman filter (ESPUKF) are proposed for mixed line-of-sight (LOS)/NLOS environments. Based on extensive simulations, the positioning accuracies of the proposed methods are found to be superior to those of conventional methods in the mildly and moderately mixed LOS/NLOS conditions. In addition, analyses are conducted on the mean square error (MSE), asymptotical unbiasedness and computational complexity of the proposed algorithms.
- URI
- https://ieeexplore.ieee.org/document/9107506https://repository.hanyang.ac.kr/handle/20.500.11754/170910
- ISSN
- 1536-1276; 1558-2248
- DOI
- 10.1109/TWC.2020.2997455
- Appears in Collections:
- RESEARCH INSTITUTE[S](부설연구소) > RESEARCH INSTITUTE OF ELECTRICAL & COMPUTER ENGINEERING(전기정보통신기술연구소) > Articles
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