Impact of Body Wearable Sensor Positions on UWB Ranging

In recent years, Ultrawideband (UWB) has become a very popular technology for time of flight (TOF) based localization and tracking applications but its human body interactions have not been studied yet extensively. Most UWB systems already proposed for pedestrian ranging have only been individually evaluated for a particular wearable sensor position. It is observed that wearable sensors mounted on or close to the human body can raise line-of-sight (LOS), quasi-line-of-sight (QLOS), and non-line-of-sight (NLOS) scenarios leading to significant ranging errors depending on the relative heading angle (RHA) between the pedestrian, wearable sensor, and anchors. In this paper, it is presented that not only does the ranging error depend on the RHA, but on the position of the wearable sensors on the pedestrian. Seven wearable sensor locations namely, fore-head, hand, chest, wrist, arm, thigh and ankle are evaluated and a fair comparison is made through extensive measurements and experiments in a multipath environment. Using the direction in which the pedestrian is facing, the RHA between the pedestrian, wearable sensor, and anchors is computed. For each wearable sensor location, an UWB ranging error model with respect to the human body shadowing effect is proposed. A final conclusion is drawn that among the aforementioned wearable locations, the fore-head provides the best range estimate because it is able to set low mean range errors of about 20 cm in multipath conditions. The fore-head’s performance is followed by the hand, wrist, ankle, arm, thigh, and chest in that order.

[1]  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.

[2]  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).

[3]  Yang Li,et al.  Investigation of Creeping Wave Propagation Around the Human Head at ISM Frequencies , 2017, IEEE Antennas and Wireless Propagation Letters.

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

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

[6]  Slawomir J. Ambroziak,et al.  An Off-Body Channel Model for Body Area Networks in Indoor Environments , 2016, IEEE Transactions on Antennas and Propagation.

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

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

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

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

[11]  Meng-Hiot Lim,et al.  A survey of problems and approaches in wireless-based indoor positioning , 2016, 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[12]  Ronald Raulefs,et al.  Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications , 2017, IEEE Communications Surveys & Tutorials.

[13]  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.

[14]  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).

[15]  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).

[16]  Andreas F. Molisch,et al.  Ultra-Wide-Band Propagation Channels , 2009, Proceedings of the IEEE.

[17]  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.

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

[19]  Fredrik Gustafsson,et al.  A NLOS-robust TOA positioning filter based on a skew-t measurement noise model , 2015, 2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

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

[21]  Fernando Seco Granja,et al.  Joint estimation of indoor position and orientation from RF signal strength measurements , 2013, International Conference on Indoor Positioning and Indoor Navigation.

[22]  José López Vicario,et al.  A Review of Pedestrian Indoor Positioning Systems for Mass Market Applications , 2017, Sensors.

[23]  Xiaofeng Yang,et al.  NLOS Mitigation for UWB Localization Based on Sparse Pseudo-Input Gaussian Process , 2018, IEEE Sensors Journal.

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

[25]  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).

[26]  Vitomir Djaja-Josko,et al.  A new map based method for NLOS mitigation in the UWB indoor localization system , 2017, 2017 25th Telecommunication Forum (TELFOR).

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