ELM-SVR error confidence fusion algorithm based on sparse fingerprint database for indoor visible light positioning system

C. Tu, J. Zhang, Z. Quan, Y. Ding, UWB indoor localization method based on neural network multi-classification for NLOS distance correction. Sens. Actuat. A-Phys. 379, 115904 (2024). https://doi.org/10.1016/j.sna.2024.115904

Article  Google Scholar 

X. Lu, K. Zhong, Z. Guan, J. Liu, A fingerprint location framework for uneven WiFi signals based on machine learning. IEEE Latin Am. Trans. 22(4), 196–213 (2024). https://doi.org/10.1109/TLA.2024.10473000

Article  Google Scholar 

C. Wu, Y. Wang, W. Ke, X. Yang, A dual-branch convolutional neural network-based bluetooth low energy indoor positioning algorithm by fusing received signal strength with angle of arrival. Mathematics 12(17), 2658 (2024). https://doi.org/10.3390/math12172658

Article  Google Scholar 

Z. Wei, J. Chen, H. Tang, H. Zhang, RSSI-based location fingerprint method for RFID indoor positioning: a review. Nondestruct. Test. Evaluat. 39(1), 3–31 (2024). https://doi.org/10.1080/10589759.2023.2253493

Article  ADS  Google Scholar 

J.C. Torres, A. Montes, S.L. Mendoza, P.R. Fernández, J.S. Betancourt, L. Escandell, C.I. Del Valle, J.M. Sánchez-Pena, A low-cost visible light positioning system for indoor positioning. Sensors 20(18), 5145 (2020). https://doi.org/10.3390/s20185145

Article  ADS  Google Scholar 

S. Bastiaens, M. Alijani, W. Joseph, D. Plets, Visible light positioning as a next-generation indoor positioning technology: a tutorial. IEEE Commun Surv Tutor. 26(4), 2867–2913 (2024). https://doi.org/10.1109/COMST.2024.3372153

Article  Google Scholar 

Z. Wu, Y. Wang, J. Fu, A hybrid RSSI and AoA indoor positioning approach with adapted confidence evaluator. Ad Hoc Netw. 154, 103375 (2024). https://doi.org/10.1016/j.adhoc.2023.103375

Article  Google Scholar 

X. Yao, H. Zhangming, W. Jiongqi, Z. Xuanying, C. Yuyun, P. Xiaogang, TOA positioning algorithm of LBL system for underwater target based on PSO. J. Syst. Eng. Electron. 34(5), 1319–1332 (2023). https://doi.org/10.23919/JSEE.2023.000107

Article  Google Scholar 

Y. Zhang, F. He, H. Zhang, H. Yang, Z. Du, Z. Xiao, TDOA and FDOA hybrid positioning of mobile radiation source with receiver position errors. Wirel. Pers. Commun. 137(1), 199–220 (2024). https://doi.org/10.1007/s11277-024-11387-7

Article  Google Scholar 

B. Chen, J. Ma, L. Zhang, J. Zhou, J. Fan, H. Lan, Research progress of wireless positioning methods based on RSSI. Electronics 13(2), 360 (2021). https://doi.org/10.3390/electronics13020360

Article  Google Scholar 

C. Jing, L. Xuan, W. Jinyuan, Z. Yonglong, Z. Junwu, An optimization method for visible light indoor positioning based on SO-CNN. Telecommun. Eng. 64(5), 702–709 (2024). https://doi.org/10.20079/j.issn.1001-893x.230616002

Article  Google Scholar 

Y. Tian, L. Jing, Z. Tong, K. Yang, D. Huang, P. Li, X. Wang, H. Huang, Z. Wang, Y. Jiang, Visible light positioning system based on stacking learning model. Opt. Commun. 578, 131479 (2025). https://doi.org/10.1016/j.optcom.2025.131479

Article  Google Scholar 

J. Zhang, X. Ke, Delineating regional BES-ELM neural networks for studying indoor visible light positioning. Photonics 11(10), 910 (2024). https://doi.org/10.3390/photonics11100910

Article  Google Scholar 

A.M.M. Abdalmajeed, M. Mahmoud, A.E.R.A. El-Fikky, H.A. Fayed, M.H. Aly, Improved indoor visible light positioning system using machine learning. Opt. Quant. Electron. 55(3), 209 (2023). https://doi.org/10.1007/s11082-022-04482-1

Article  Google Scholar 

Y. Mei, Y. Deng, Indoor visible light fingerprint location method based on marine predator algorithm-optimized least squares support vector machine. Appl. Sci. 14(16), 7416 (2024). https://doi.org/10.3390/app14167416

Article  Google Scholar 

W. Yang, L. Qin, X. Hu, D. Zhao, Indoor visible-light 3D positioning system based on GRU neural network. Photonics 10(6), 633 (2024). https://doi.org/10.3390/photonics10060633

Article  Google Scholar 

N.B. Fite, G.M. Wegari, H. Steendam, Integration of artificial neural network regression and principal component analysis for indoor visible light positioning. Sensors 25(4), 1049 (2025). https://doi.org/10.3390/s25041049

Article  Google Scholar 

Y.H. Shu, Y.H. Chang, Y.Z. Lin, C.W. Chou, Real-time indoor visible light positioning (VLP) using long short term memory neural network (LSTM-NN) with principal component analysis (PCA). Sensors 24(16), 5424 (2024). https://doi.org/10.3390/s24165424

Article  Google Scholar 

H.Q. Tran, C. Ha, Machine learning in indoor visible light positioning systems: a review. Neurocomputing 491, 117–131 (2022). https://doi.org/10.1016/j.neucom.2021.10.123

Article  Google Scholar 

N. Chaudhary, O.I. Younus, L.N. Alves, Z. Ghassemlooy, S. Zvanovec, H. Le-Minh, An indoor visible light positioning system using tilted leds with high accuracy. Sensors 21(3), 920 (2021). https://doi.org/10.3390/s21030920

Article  ADS  Google Scholar 

R. Liu, Z. Liang, Z. Wang, W. Li, Indoor visible light positioning based on improved whale optimization method with min-max algorithm. IEEE Trans. Instrum. Meas. 72, 1–10 (2023). https://doi.org/10.1109/TIM.2023.3240212

Article  Google Scholar 

B. Hou, Y. Wang, RF-KELM indoor positioning algorithm based on WiFi RSS fingerprint. Meas. Sci. Technol. 35(4), 045004 (2024). https://doi.org/10.1088/1361-6501/ad1873

Article  ADS  Google Scholar 

J. Bi, M. Zhao, G. Yao, H. Cao, Y. Feng, H. Jiang, D. Chai, PSOSVRPos: WiFi indoor positioning using SVR optimized by PSO. Expert Syst. Appl. 222, 119778 (2023). https://doi.org/10.1016/j.eswa.2023.119778

Article  Google Scholar 

I.M. Abou-Shehada, A.F. AlMuallim, A.W.K. AlFaqeh, A.H. Muqaibel, K.H. Park, M.S. Alouini, Accurate indoor visible light positioning using a modified pathloss model with sparse fingerprints. J. Lightwave Technol. 39(20), 6487–6497 (2021). https://doi.org/10.1109/JLT.2021.3098005

Article  ADS  Google Scholar 

Y.C. Wu, K.L. Hsu, Y. Liu, C.Y. Hong, C.W. Chow, C.H. Yeh, X.L. Liao, K.H. Lin, Y.Y. Chen, Using linear interpolation to reduce the training samples for regression based visible light positioning system. IEEE Photonics J. 12(2), 1–5 (2020). https://doi.org/10.1109/JPHOT.2020.2975213

Article  Google Scholar 

Y. Xing, Q. Song, G. Cheng, Benefit of interpolation in nearest neighbor algorithms. SIAM J. Math. Data Sci. 4(2), 935–956 (2020). https://doi.org/10.1137/21M1437457

Article  MathSciNet  Google Scholar 

J. Hu, H. Liu, D. Liu, Z. Yan, K. Xu, Reducing Wi-Fi fingerprint collection based on affinity propagation clustering and WKNN interpolation algorithm. IMCEC (2018). https://doi.org/10.1109/IMCEC.2018.8469697

Article  Google Scholar 

Comments (0)

No login
gif