Effects of the Body Wearable Sensor Position on the UWB Localization Accuracy

In recent years, several Ultrawideband (UWB) localization systems have already been proposed and evaluated for accurate position estimation of pedestrians. However, most of them are evaluated for a particular wearable sensor position; hence the accuracy obtained is subject to a given wearable sensor position. In this paper, we study the effects of body wearable sensor positions i.e., chest, arm, ankle, wrist, thigh, fore-head, hand, on the localization accuracy. The conclusion drawn is that the fore-head is the best, and the chest is the worst body sensor location for tracking a pedestrian. While the fore-head position is able to set an error lower than 0.35 m (90th percentile), the chest is able to set 4 m. The reason for such a contrast in the performance lies in the fact that in NLOS situations, the chest as an obstacle is larger in size and thickness than any other part of the human body, which the UWB signal needs to overcome to reach the target wearable sensor. And so, the large errors arise due to the signal arriving at the target wearable sensor from reflections of a nearby object or a wall in the environment.

[1]  Stefano Paolucci,et al.  Wearable inertial sensors for human movement analysis , 2016, Expert review of medical devices.

[2]  Akram Alomainy,et al.  Experimental Investigation of 3-D Human Body Localization Using Wearable Ultra-Wideband Antennas , 2015, IEEE Transactions on Antennas and Propagation.

[3]  Kaveh Pahlavan,et al.  Emerging opportunities for localization and tracking [Guest Editorial] , 2011, IEEE Wirel. Commun..

[4]  Christian Wietfeld,et al.  Design of an UWB indoor-positioning system for UAV navigation in GNSS-denied environments , 2015, 2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[5]  Simon Schmitt,et al.  The effects of human body shadowing in RF-based indoor localization , 2014, 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[6]  Federica Pascucci,et al.  Hybrid Indoor Positioning System for First Responders , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[7]  Robert Piché,et al.  A Survey of Selected Indoor Positioning Methods for Smartphones , 2017, IEEE Communications Surveys & Tutorials.

[8]  Myo-Taeg Lim,et al.  Improving Reliability of Particle Filter-Based Localization in Wireless Sensor Networks via Hybrid Particle/FIR Filtering , 2015, IEEE Transactions on Industrial Informatics.

[9]  Haishu Ma,et al.  Fusion of RSS and Phase Shift Using the Kalman Filter for RFID Tracking , 2017, IEEE Sensors Journal.

[10]  I. Dove,et al.  Analysis of Radio Propagation Inside the HumanBody for in-Body Localization Purposes , 2014 .

[11]  Jianping Pan,et al.  Modeling, validation and performance evaluation of body shadowing effect in ultra-wideband networks , 2009, Phys. Commun..

[12]  Kaveh Pahlavan,et al.  Modeling the effect of human body on TOA ranging for indoor human tracking with wrist mounted sensor , 2013, 2013 16th International Symposium on Wireless Personal Multimedia Communications (WPMC).

[13]  M. Petovello,et al.  A Stand-Alone Approach for High-Sensitivity GNSS Receivers in Signal-Challenged Environment , 2017, IEEE Transactions on Aerospace and Electronic Systems.

[14]  Shiban K. Koul,et al.  Experimental Analysis of Ultra-Wideband Body-to-Body Communication Channel Characterization in an Indoor Environment , 2019, IEEE Transactions on Antennas and Propagation.

[15]  Gustavo Pessin,et al.  Wearable computing for railway environments: proposal and evaluation of a safety solution , 2017 .

[16]  Wu Chen,et al.  A New Indoor Positioning System Architecture Using GPS Signals , 2015, Sensors.

[17]  Yong J. Yuan,et al.  Wearable Medical Monitoring Systems Based on Wireless Networks: A Review , 2016, IEEE Sensors Journal.

[18]  Kaveh Pahlavan,et al.  Toward Accurate Human Tracking: Modeling Time-of-Arrival for Wireless Wearable Sensors in Multipath Environment , 2014, IEEE Sensors Journal.

[19]  Mark L. Fowler,et al.  Accurate Localization of In-Body Medical Implants Based on Spatial Sparsity , 2014, IEEE Transactions on Biomedical Engineering.

[20]  Fernando Seco Granja,et al.  Comparing Decawave and Bespoon UWB location systems: Indoor/outdoor performance analysis , 2016, 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[21]  Muhammad Diono,et al.  Indoor positioning system based on received signal strength (RSS) fingerprinting: Case in Politeknik Caltex Riau , 2014, 2014 8th International Conference on Telecommunication Systems Services and Applications (TSSA).

[22]  P. Puricer,et al.  Technical Limitations of GNSS Receivers in Indoor Positioning , 2007, 2007 17th International Conference Radioelektronika.

[23]  Subhas Chandra Mukhopadhyay,et al.  Wearable Sensors for Human Activity Monitoring: A Review , 2015, IEEE Sensors Journal.

[24]  Pawel Kulakowski,et al.  Angle-of-arrival localization based on antenna arrays for wireless sensor networks , 2010, Comput. Electr. Eng..

[25]  Angelica Munoz-Melendez,et al.  Wearable Inertial Sensors for Human Motion Analysis: A Review , 2016, IEEE Sensors Journal.

[26]  N. Kuster,et al.  The dependence of electromagnetic energy absorption upon human head tissue composition in the frequency range of 300-3000 MHz , 2000 .

[27]  Fernando Seco Granja,et al.  Comparing Ubisense, BeSpoon, and DecaWave UWB Location Systems: Indoor Performance Analysis , 2017, IEEE Transactions on Instrumentation and Measurement.

[28]  Akiko Sato,et al.  Pedestrian Dead Reckoning using adaptive particle filter to human moving mode , 2013, International Conference on Indoor Positioning and Indoor Navigation.

[29]  Kevin I-Kai Wang,et al.  Human Body Shadowing Effect on UWB-Based Ranging System for Pedestrian Tracking , 2019, IEEE Transactions on Instrumentation and Measurement.

[30]  Mark J. Bentum,et al.  The effect of human-body shadowing on indoor UWB TOA-based ranging systems , 2012, 2012 9th Workshop on Positioning, Navigation and Communication.

[31]  Kaveh Pahlavan,et al.  An empirical channel model for the effect of human body on ray tracing , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[32]  Alice Buffi,et al.  Numerical Investigation of an UWB Localization Technique for Unmanned Aerial Vehicles in Outdoor Scenarios , 2017, IEEE Sensors Journal.

[33]  Peio Lopez-Iturri,et al.  Impact of Body Wearable Sensor Positions on UWB Ranging , 2019, IEEE Sensors Journal.

[34]  Ali Jasim Ramadhan Wearable Smart System for Visually Impaired People , 2018, Sensors.

[35]  Daniele Comotti,et al.  Static and Dynamic Accuracy of an Innovative Miniaturized Wearable Platform for Short Range Distance Measurements for Human Movement Applications , 2017, Sensors.

[36]  André P. Catarino,et al.  Performance Analysis of ToA-Based Positioning Algorithms for Static and Dynamic Targets with Low Ranging Measurements , 2017, Sensors.

[37]  Alfonso Bahillo,et al.  Step Length Estimation Using UWB Technology: A Preliminary Evaluation , 2018, 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[38]  S Lanzisera,et al.  Radio Frequency Time-of-Flight Distance Measurement for Low-Cost Wireless Sensor Localization , 2011, IEEE Sensors Journal.

[39]  T. Samaras,et al.  The dependence of electromagnetic far-field absorption on body tissue composition in the frequency range from 300 MHz to 6 GHz , 2006, IEEE Transactions on Microwave Theory and Techniques.

[40]  Ilona Buchem,et al.  Gamification designs in Wearable Enhanced Learning for healthy ageing , 2015, 2015 International Conference on Interactive Mobile Communication Technologies and Learning (IMCL).

[41]  Fei Liu,et al.  CC-KF: Enhanced TOA Performance in Multipath and NLOS Indoor Extreme Environment , 2014, IEEE Sensors Journal.

[42]  Kaveh Pahlavan,et al.  Modeling indoor TOA ranging error for body mounted sensors , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[43]  Ran Liu,et al.  Localization of Moving Objects Based on RFID Tag Array and Laser Ranging Information , 2019, Electronics.

[44]  A. Wittneben,et al.  UWB signal propagation at the human head , 2006, IEEE Transactions on Microwave Theory and Techniques.

[45]  Z. Irahhauten,et al.  UWB channel measurements and results for wireless personal area networks applications , 2005, The European Conference on Wireless Technology, 2005..

[46]  Francisco Falcone,et al.  FDTD and Empirical Exploration of Human Body and UWB Radiation Interaction on TOF Ranging , 2019, IEEE Antennas and Wireless Propagation Letters.

[47]  Gonzalo Seco-Granados,et al.  Challenges in Indoor Global Navigation Satellite Systems: Unveiling its core features in signal processing , 2012, IEEE Signal Processing Magazine.

[48]  Matteo Ridolfi,et al.  Experimental Evaluation of UWB Indoor Positioning for Sport Postures , 2018, Sensors.

[49]  Ramon Villarino,et al.  Wireless Wearable Magnetometer-Based Sensor for Sleep Quality Monitoring , 2018, IEEE Sensors Journal.

[50]  Cheng Xu,et al.  MCC-CKF: A Distance Constrained Kalman Filter Method for Indoor TOA Localization Applications , 2019, Electronics.

[51]  Vassilis Gikas,et al.  Evaluation of Range Error Calibration Models for Indoor UWB Positioning Applications , 2018, 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN).