Abstract
In the study of indoor visible light localization, a matrix-based fingerprint library construction method is used to recover the data in the offline phase. While in the online matching and positioning phase, the Stagewise Orthogonal Matching Pursuit algorithm in compressed sensing theory is improved and introduced into indoor visible light localization. After simulation, the average error is 0.027 m. Then we verify the advancement of this algorithm by comparing with other algorithms applied to visible light localization. The experimental verification shows that the error is only 0.029 m.
Similar content being viewed by others
References
Aminikashani, M., Gu, W., Kavehrad, M.: Indoor positioning with OFDM visible light communications. In: 2016 IEEE Consumer Communications & Networking Conference. IEEE (2016)
Ang, K.H., Chong, G., Li, Y.: PID control system analysis, design, and technology. IEEE Trans. Control Syst. Technol. 13(4), 559–576 (2015)
Bartier, P.M., Keller, C.P.: Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW). Comput. Geosci. 22(7), 795–799 (1996)
Blomgren, P., Chan, T.F.: Color TV: total variation methods for restoration of vector valued images. IEEE Trans. Image Process. 7(3), 304–309 (1998)
Candès, E.J., Tao, T.: The power of convex relaxation: near-optimal matrix completion. IEEE Press 4(6), 2053–2080 (2010)
Chen, Y.-A., Chang, Y.-T., Tseng, Y.-C., Chen, W.-T.: A framework for simultaneous message broadcasting using CDMA-Based visible light communications. IEEE Sensors J. 15(12), 6819–6827 (2015)
Chi, N., Shi, M.: Advanced modulation formats for underwater visible light communications. Chin. Opt. Lett. 16(12), 120603 (2018)
Cossu, G., et al.: A visible light location aided optical wireless system. In: 2011 IEEE Globecom Workshops (GC Wkshps). IEEE (2012)
Gu, W., Aminikashani, M., Deng, P., Kavehrad, M.: Impact of multipath reflections on the performances of indoor visible light positioning systems. J. Lightwave Technol. 34(10), 2578–2587 (2016)
Guan, W., Wu, Y., Wen, S.: Errata: high precision three-dimensional iterative indoor localization algorithm using code division multiple access modulation based on visible light communication. Opt. Eng. 55(11), 119801 (2016)
He, S., Chan, S.-H.G.: Wi-fi fingerprint-based indoor positioning recent advances and comparisons. IEEE Commun. Surv. Tutor. 18(1), 466–490 (2015)
Jung, S.-Y., Hann, S., Park, C.-S.: TDOA-based optical wireless indoor localization using LED ceiling lamps. IEEE Trans. Consum. Electron. 57(4), 1592–1597 (2011)
Khalajmehrabadi, A., Gatsis, N., Akopian, D.: Modern WLAN fingerprinting indoor positioning methods and deployment challenges. IEEE Commun. Surv. Tutor. 19(3), 1974–2002 (2017)
Kim, H.-S., Kim, D.-R., Yang, S.-H., Son, Y.-H., Han, S.-K.: An indoor visible light communication positioning system using a RF carrier allocation technique. J. Lightwave Technol. 31(1), 134–144 (2013)
Krumm, J., Platt, J.: Minimizing calibration efforts for an indoor 802.11 device location measurement system. In: Nips (2003)
Kuo, S.-P., Tseng, Y.-C.: Discriminant minimization search for large-scale RF-based localization systems. IEEE. Trans. Mob. Comput. 10(2), 291–304 (2011)
Li, B.H., Salter, J., Dempster, A.G., Rizos, C.: Indoor positioning techniques based on wireless LAN. In: 1st IEEE International Conference on Wireless Broadband and Ultra Wideband Communications, Sydney, pp. 13–16 (2006)
Lou, P., Zhang, H.M., Zhang, X., Yao, M., Xu, Z.: Fundamental analysis for indoor visible light positioning system. In: 2012 1st IEEE International Conference on Communications in China Workshops, Bejing, pp. 59–63 (2012)
Needell, D., Tropp, J.A.: CoSAMP: iterative signal recovery from incomplete and inaccurate samples. Appl. Comput. Harmon. Anal. 26(3), 301–321 (2009)
Needell, D., Vershynin, R.: Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit. IEEE J. Sel. Top. Signal Process. 4(2), 310–316 (2010)
Pasha, M.A., Yuen, C., Hassan, N.U.: Indoor positioning system designs using visible LED lights: performance comparison of TDM and FDM protocols. Electron. Lett. 51(1), 72–74 (2015)
Pati, Y.C., Rezaiifar, R., Krishnaprasad, P.S.: Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition. In: Proceedings of 27th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, pp. 40–44 (1993)
Shi, B.S., Lian, Q.S., Chen, S.Z., Tian, Y., Fan, X.Y.: Coded diffraction imaging via double sparse regularization model. Digit. Signal Process. 79, 23–33 (2018)
Swangmuang, N., Krishnamurthy, P.: An effective location fingerprint model for wireless indoor localization. Pervasive Mob. Comput. 4(6), 836–850 (2008)
Yang, J.F., Zhang, Y., Yin, W.T.: A fast alternating direction method for tvl1-l2 signal reconstruction from partial fourier data. IEEE J. Sel. Topics Signal Process 4(2), 288–297 (2010)
Zheng, Z.L., Zhang, H.X., Jia, J., Zhao, J.M., Guo, L., Fu, F.M., Yu, M.D.: Low-rank matrix recovery with discriminant regularization. In: Lect. Notes. Comput. Sci., vol. 7819(2), pp. 437–448 (2013)
Zsolczai, V., Szabo, G., Feher, G., et al.: Experimental investigation of multiplexing methods in visible light communication system for indoor positioning. In: 2016 18th International Conference on Transparent Optical Networks (ICTON). IEEE (2016)
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Shen, H., Shao, J., Zuo, X. et al. Indoor visible light localization based on compressed sensing under matrix filling recovery. Opt Quant Electron 52, 206 (2020). https://doi.org/10.1007/s11082-020-02322-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11082-020-02322-8