[1] Siddig A, Bleakley C J, Makki A, et al. High-resolution time of arrival estimation for OFDM-based transceivers[J]. Electronics Letters, 2015, 51(3):294-296.
[2] Pak J M, Ahn C K, Shi Peng, et al. Distributed hybrid particle FIR filtering for mitigating NLOS effects in TOA-based localization using wireless sensor networks[J]. IEEE Transactions on Industrial Electronics, 2017, 64(6):5182-5191.
[3] Silva B, Hancke G P. IR-UWB-based non-line-of-sight identification in harsh environments:principles and challenges[J]. IEEE Transactions on Industrial Informatics, 2016, 12(3):1188-1195.
[4] Xiao Zhuoling, Wen Hongkai, Markham A, et al. Non-line-of-sight identification and mitigation using received signal strength[J]. IEEE Transactions on Wireless Communications, 2015, 14(3):1689-1702.
[5] Li Xiaohui, Cai Xiong, Hei Yongqiang, et al. NLOS identification and mitigation based on channel state information for indoor WiFi localization[J]. IET Communications, 2017, 11(4):531-537.
[6] Chitambira B, Armour S, Wales S, et al. NLOS identification and mitigation for geolocation using least-squares support vector machines[C]//2017 IEEE Wireless Communications and Networking Conference(WCNC). New York:IEEE Press, 2017:1-6.
[7] Yan Jun, Wu Lenan. A data fusion scheme for modified EKF banks positioning algorithm in mixed LOS/NLOS conditions[C]//12th IEEE International Conference on Ubiquitous Intelligence and Computing and 15th IEEE International Conference on Autonomic and Trusted Computing and 15th IEEE International Conference on Scalable Computing and Communications and Its Associated Workshops(UIC-ATC-ScalCom). New York:IEEE Press, 2015:1249-1252.
[8] Zhang Lan, Chen Feng, Yu Yao. Research on hybrid location algorithm with high accuracy in indoor environment[C]//34th Chinese Control Conference. New York:IEEE Press, 2015:15454267.
[9] Hu Nan, Wu Chengdong, Li Chen, et al. The NLOS localization algorithm based on the linear regression model of extended Kalman filter[J]. Journal of Image and Graphics, 2016, 4(2):141-144.
[10] Wang Hongwei, Li Hongbin, Zhang Wei, et al. A unified framework for M-estimation based robust Kalman smoothing[J]. Signal Processing, 2019, 158:61-65. |