Acta Optica Sinica, Volume. 42, Issue 5, 0506002(2022)
Research on Visible Light Indoor Localization Algorithm Based on Elman Neural Network
[1] Yuan C L, Lu H M, Huang J C et al. Energy self-sustaining visible light positioning algorithm based on clustering[J]. Acta Optica Sinica, 41, 1006001(2021).
[2] Zhao C H, Zhang H M, Song J. Fingerprint based visible light indoor localization method[J]. Chinese Journal of Lasers, 45, 0806002(2018).
[3] Cao Y, Dang Y C, Peng X F et al. Indoor visible light localization method using TOA/RSS hybrid information[J]. Chinese Journal of Lasers, 48, 0100001(2021).
[4] Dong W J, Wang X D, Wu N. A hybrid RSS/AOA algorithm for indoor visible light positioning[J]. Laser & Optoelectronics Progress, 55, 050603(2018).
[5] Yang Z C, Wang Z Y, Zhang J S et al. Polarization-based visible light positioning[J]. IEEE Transactions on Mobile Computing, 18, 715-727(2019).
[6] Almadani Y, Ijaz M, Adebisi B et al. An experimental evaluation of a 3D visible light positioning system in an industrial environment with receiver tilt and multipath reflections[J]. Optics Communications, 483, 126654(2021).
[7] Wang W G, Zhang Y W, Tian L B. TOA-based NLOS error mitigation algorithm for 3D indoor localization[J]. China Communications, 17, 63-72(2020).
[8] Liu C F, Yang J, Wang F S. Joint TDOA and AOA location algorithm[J]. Journal of Systems Engineering and Electronics, 24, 183-188(2013).
[9] Li S P, Yang X Y, Zhao R et al. An indoor positioning method based on RSSI probability distribution[J]. IOP Conference Series: Materials Science and Engineering, 490, 042054(2019).
[10] Gao L, Yang X M. An improved trilateration positioning algorithm[J]. Industry and Mine Automation, 46, 78-81(2020).
[11] Xie C Y, Guan W P, Wu Y X et al. The LED-ID detection and recognition method based on visible light positioning using proximity method[J]. IEEE Photonics Journal, 10, 1-16(2018).
[12] Wang Y F, Gao J X, Li Z K et al. Robust and accurate Wi-Fi fingerprint location recognition method based on deep neural network[J]. Applied Sciences, 10, 321(2020).
[13] Zhang H Y, Yu H Y, Chen L L. Indoor visible light location using adaptive pollination receiving signal strength indication based on reverse learning strategy[J]. Chinese Journal of Lasers, 48, 0106001(2021).
[14] Tran H, Ha C. Improved visible light-based indoor positioning system using machine learning classification and regression[J]. Applied Sciences, 9, 1048(2019).
[15] Raes W, Knudde N, De Bruycker J et al. Experimental evaluation of machine learning methods for robust received signal strength-based visible light positioning[J]. Sensors, 20, 6109(2020).
[16] Şahin A. Ero lu Y S, Güvenç i, et al. Hybrid 3-D localization for visible light communication systems[J]. Journal of Lightwave Technology, 33, 4589-4599(2015).
[17] Xu Y, Wang X X. Indoor positioning algorithm of subregional visible light based on multilayer ELM[J]. Journal of Hunan University (Natural Sciences), 46, 125-132(2019).
[18] Xiao J L, Yue D W, Zhao Z D et al. A visible light localization algorithm based on BP neural network optimized by genetic algorithm[J]. Journal of Optoelectronics·Laser, 30, 810-816(2019).
[19] Wang Z, Zhu Y Y, Zhang Z C. Indoor visible light location system based on BP neural network[J]. Science & Technology Information, 19, 81-84(2021).
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Ling Qin, Chongtai Zhang, Ying Guo, Yanhong Xu, Fengying Wang, Xiaoli Hu. Research on Visible Light Indoor Localization Algorithm Based on Elman Neural Network[J]. Acta Optica Sinica, 2022, 42(5): 0506002
Category: Fiber Optics and Optical Communications
Received: Jul. 19, 2021
Accepted: Sep. 10, 2021
Published Online: Mar. 8, 2022
The Author Email: Hu Xiaoli (huxiaoli@imust.edu.cn)