A High-Precision Positioning Scheme Under Non-Point Visible Transmitters

An interacting multiple model based on unscented Kalman filter (IMM-UKF) is widely applied to positioning and tracking targets in various tracking scenarios. At the same time, visible light positioning (VLP) is developing rapidly due to the low cost and accuracy. Therefore, indoor positioning and tracking based on VLP combined with the IMM-UKF has attracted considerable interest. However, existing algorithms work on the assumption that the light-emitting diodes used for tracking are all point light sources, which ignores the geometry of these transmitters and results in low tracking accuracy. To overcome this problem, this paper proposes an innovative tracking algorithm based on VLP. This algorithm considers the shapes of the lights in combination with existing tracking algorithms, such as IMM-UKF. Simulation results show that in a standard Gaussian noise environment, the larger the transmitter is, the more meaningful the proposed algorithm is.

[1]  Chung Shue Chen,et al.  Location-based information transmission systems using visible light communications , 2017, Trans. Emerg. Telecommun. Technol..

[2]  Hong Wang,et al.  UKF Based Nonlinear Filtering Using Minimum Entropy Criterion , 2013, IEEE Transactions on Signal Processing.

[3]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[4]  Pengfei Du,et al.  Robust 3D Indoor VLP System Based on ANN Using Hybrid RSS/PDOA , 2019, IEEE Access.

[5]  Yim-Fun Hu,et al.  Automatic Modulation Classification Using Interacting Multiple Model Kalman Filter for Channel Estimation , 2019, IEEE Transactions on Vehicular Technology.

[6]  John Thompson,et al.  A Survey of Positioning Systems Using Visible LED Lights , 2018, IEEE Communications Surveys & Tutorials.

[7]  Yang Liu,et al.  Analysis of Kalman Filter Innovation-Based GNSS Spoofing Detection Method for INS/GNSS Integrated Navigation System , 2019, IEEE Sensors Journal.

[8]  Hiroshi Saito,et al.  Adaptive Filtering Methods for RSSI Signals in a Device-Free Human Detection and Tracking System , 2019, IEEE Systems Journal.

[9]  Chang Liu,et al.  Parallel Interacting Multiple Model-Based Human Motion Prediction for Motion Planning of Companion Robots , 2015, IEEE Transactions on Automation Science and Engineering.

[10]  Lennart Svensson,et al.  Moment Estimation Using a Marginalized Transform , 2012, IEEE Transactions on Signal Processing.

[11]  Sinan Gezici,et al.  Improved Lower Bounds for Ranging in Synchronous Visible Light Positioning Systems , 2016, Journal of Lightwave Technology.

[12]  Jiancheng Fang,et al.  An Implicit UKF for Satellite Stellar Refraction Navigation System , 2017, IEEE Transactions on Aerospace and Electronic Systems.

[13]  Chunquan Li,et al.  Natural Human–Robot Interface Using Adaptive Tracking System with the Unscented Kalman Filter , 2020, IEEE Transactions on Human-Machine Systems.

[14]  S. Haykin,et al.  Cubature Kalman Filters , 2009, IEEE Transactions on Automatic Control.

[15]  Adrian Neild,et al.  Visible light positioning: a roadmap for international standardization , 2013, IEEE Commun. Mag..

[16]  Yuegang Fu,et al.  Theoretical Accuracy Analysis of Indoor Visible Light Communication Positioning System Based on Received Signal Strength Indicator , 2014, Journal of Lightwave Technology.

[17]  Changyuan Yu,et al.  A 3-D high accuracy positioning system based on visible light communication with novel positioning algorithm , 2017 .

[18]  Mohsen Kavehrad,et al.  Impact of Multipath Reflections on the Performance of Indoor Visible Light Positioning Systems , 2015, Journal of Lightwave Technology.

[19]  Yuichi Motai,et al.  Tracking Human Motion With Multichannel Interacting Multiple Model , 2013, IEEE Transactions on Industrial Informatics.

[20]  John Cosmas,et al.  Experimental testbed for VLC-based localization framework in 5G Internet of Radio Light , 2019, 2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS).

[21]  S. Gezici,et al.  Comparative Theoretical Analysis of Distance Estimation in Visible Light Positioning Systems , 2016, Journal of Lightwave Technology.

[22]  Badri N. Vellambi,et al.  Indoor Positioning System Using Visible Light and Accelerometer , 2014, Journal of Lightwave Technology.

[23]  Tae-Kyung Sung,et al.  Comparisons of error characteristics between TOA and TDOA positioning , 2002 .

[24]  Martin Johnston,et al.  Robust GPS Carrier Tracking Model Using Unscented Kalman Filter for a Dynamic Vehicular Communication Channel , 2018, IEEE Access.

[25]  Wojciech Mazurczyk,et al.  5G Internet of radio light services for Musée de la Carte à Jouer , 2018, 2018 Global LIFI Congress (GLC).

[26]  Gourab Sen Gupta,et al.  An Accurate Visible Light Positioning System Using Regenerated Fingerprint Database Based on Calibrated Propagation Model , 2019, IEEE Transactions on Instrumentation and Measurement.

[27]  Lang Hong,et al.  Multirate interacting multiple model filtering for target tracking using multirate models , 1999, IEEE Trans. Autom. Control..

[28]  Thomas Q. Wang,et al.  Theoretical Lower Bound for Indoor Visible Light Positioning Using Received Signal Strength Measurements and an Aperture-Based Receiver , 2017, Journal of Lightwave Technology.

[29]  Hartmut Brauer,et al.  A Hall-Sensor-Based Localization Method With Six Degrees of Freedom Using Unscented Kalman Filter , 2019, IEEE Sensors Journal.

[30]  Yingwei Zhao,et al.  Cubature + Extended Hybrid Kalman Filtering Method and Its Application in PPP/IMU Tightly Coupled Navigation Systems , 2015, IEEE Sensors Journal.

[31]  Yonggang Zhang,et al.  A New Process Uncertainty Robust Student’s t Based Kalman Filter for SINS/GPS Integration , 2017, IEEE Access.

[32]  Xian Jin,et al.  Design and Implementation of an Optical Receiver for Angle-of-Arrival-Based Positioning , 2017, Journal of Lightwave Technology.

[33]  John Cosmas,et al.  5G Internet of Radio Light Positioning System for Indoor Broadcasting Service , 2020, IEEE Transactions on Broadcasting.