Joint Measurement and Trajectory Recovery in Visible Light Communication

The growing preponderance of light emitting diodes (LEDs) for lighting has motivated research into their dual use for visible light communication (VLC) and navigation. VLC extracts a bit sequence from a series of photodetector scans. Among this data is an LED ID that ensures the reliable data association in navigation and data communication. Recovering the LED data and ID requires the accurate prediction of each LED's projected position on the photodetector array to extract efficiently and reliably the LED ON-OFF status in each photodetector scan. Estimating the LED projected position is challenging because: 1) clutter and noise corrupt the measurements; 2) the LED status will be OFF in some scans; and 3) the predicted projection location sequence depends on the estimated rover state trajectory, which is uncertain and time varying. This paper presents a method to determine the q-most probable data and the LED position sequences simultaneously for a time window of data, using Bayesian multiple hypothesis tracking techniques by maximizing the posterior probabilities. This paper focuses on the VLC data and the LED position sequence extraction, which includes rover state estimation. Implementation of the multiple hypothesis tracking algorithm is illustrated by postprocessed experimental results.

[1]  Ingemar J. Cox,et al.  An Efficient Implementation of Reid's Multiple Hypothesis Tracking Algorithm and Its Evaluation for the Purpose of Visual Tracking , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[3]  Neal Lesh,et al.  Indoor navigation using a diverse set of cheap, wearable sensors , 1999, Digest of Papers. Third International Symposium on Wearable Computers.

[4]  Padhraic Smyth,et al.  A graphical model representation of the track-oriented multiple hypothesis tracker , 2012, 2012 IEEE Statistical Signal Processing Workshop (SSP).

[5]  Jay A. Farrell,et al.  Navigation using linear photo detector arrays , 2013, 2013 IEEE International Conference on Control Applications (CCA).

[6]  Masao Nakagawa,et al.  Indoor visible communication utilizing plural white LEDs as lighting , 2001, 12th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications. PIMRC 2001. Proceedings (Cat. No.01TH8598).

[7]  Stergios I. Roumeliotis,et al.  A Multi-State Constraint Kalman Filter for Vision-aided Inertial Navigation , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[8]  Jean-Yves Bouguet,et al.  Camera calibration toolbox for matlab , 2001 .

[9]  Jay A. Farrell,et al.  Indoor localization based on LEDs , 2011, 2011 IEEE International Conference on Control Applications (CCA).

[10]  Katta G. Murty,et al.  Letter to the Editor - An Algorithm for Ranking all the Assignments in Order of Increasing Cost , 1968, Oper. Res..

[11]  Toshiaki Fujii,et al.  Feasible Study of Road-to-Vehicle Communication System Using LED Array and High-Speed Camera , 2008 .

[12]  Jay A. Farrell,et al.  Real-Time Computer Vision/DGPS-Aided Inertial Navigation System for Lane-Level Vehicle Navigation , 2012, IEEE Transactions on Intelligent Transportation Systems.

[13]  Y. Bar-Shalom.  Tracking and data association , 1988 .

[14]  Dongfang Zheng.  Joint Visible Light Communication and Navigation via LEDs , 2014 .

[15]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[16]  A. Volgenant,et al.  A shortest augmenting path algorithm for dense and sparse linear assignment problems , 1987, Computing.

[17]  Shinichiro Haruyama.  Advances in visible light communication technologies , 2012, 2012 38th European Conference and Exhibition on Optical Communications.

[18]  Tom Drummond,et al.  Machine Learning for High-Speed Corner Detection , 2006, ECCV.

[19]  Y. Bar-Shalom,et al.  The probabilistic data association filter , 2009, IEEE Control Systems.

[20]  Roberto Brunelli,et al.  Advanced , 1980 .

[21]  Shinichiro Haruyama.  Visible light communications , 2010, 36th European Conference and Exhibition on Optical Communication.

[22]  Yaakov Bar-Shalom,et al.  The dimensionless score function for multiple hypothesis decision in tracking , 2005, 2005 IEEE International Conference on Systems, Man and Cybernetics.

[23]  Zhengyou Zhang,et al.  Flexible camera calibration by viewing a plane from unknown orientations , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[24]  James R. Bergen,et al.  Visual odometry , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[25]  D. Bertsekas.  The auction algorithm: A distributed relaxation method for the assignment problem , 1988 .

[26]  Kamran Kiasaleh.  Performance analysis of free-space on-off-keying optical communication systems impaired by turbulence , 2002, SPIE LASE.

[27]  Masao Nakagawa,et al.  Integrated system of white LED visible-light communication and power-line communication , 2003, IEEE Trans. Consumer Electron..

[28]  Hans P. Moravec.  Obstacle avoidance and navigation in the real world by a seeing robot rover , 1980 .

[29]  Christopher G. Harris,et al.  3D positional integration from image sequences , 1988, Image Vis. Comput..

[30]  Marios M. Polycarpou,et al.  Command filtered adaptive backstepping , 2010, Proceedings of the 2010 American Control Conference.

[31]  Joachim Walewski,et al.  High-Speed Wireless Indoor Communication via Visible Light , 2007 .

[32]  Jay A. Farrell,et al.  An algorithm to recover an LED path , 2014, 2014 European Control Conference (ECC).

[33]  V. Macellari,et al.  CoSTEL: a computer peripheral remote sensing device for 3-dimensional monitoring of human motion , 1983, Medical and Biological Engineering and Computing.

[34]  John Nicholson,et al.  RFID in robot-assisted indoor navigation for the visually impaired , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[35]  Kurt Konolige,et al.  CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching , 2008, ECCV.

[36]  Shigeru Shimamoto,et al.  Foundational analysis of spatial optical wireless communication utilizing image sensor , 2011, 2011 IEEE International Conference on Imaging Systems and Techniques.

[37]  Roberto Brunelli,et al.  Template Matching Techniques in Computer Vision: Theory and Practice , 2009 .

[38]  Jay A. Farrell,et al.  Aided Navigation: GPS with High Rate Sensors , 2008 .

[39]  J. Farrell,et al.  LED path recovery in a moving sensor , 2014 .

[40]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[41]  Toshiaki Fujii,et al.  Improved Decoding Methods of Visible Light Communication System for ITS Using LED Array and High-Speed Camera , 2010, 2010 IEEE 71st Vehicular Technology Conference.

[42]  Masao Nakagawa,et al.  Indoor Visible Light Data Transmission System Utilizing White LED Lights , 2003 .

[43]  Mohsen Kavehrad.  Broadband room service by light. , 2007 .

[44]  Harald Haas,et al.  Visible light communication using OFDM , 2006, 2nd International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities, 2006. TRIDENTCOM 2006..

[45]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[46]  Jay A. Farrell,et al.  LED-based initialization and navigation , 2013, 2013 American Control Conference.

[47]  Masao Nakagawa,et al.  Fundamental analysis for visible-light communication system using LED lights , 2004, IEEE Transactions on Consumer Electronics.

[48]  D. Massart,et al.  The Mahalanobis distance , 2000 .