Performance Comparison of Sensor Implemented in Smartphones with X-IMU

In this paper a comparison of inertial sensors in smartphones and X-IMU (Inertial Measurement Unit) is presented. The goal of the experiment is to compare the performance of inertial sensors implemented in smartphones with special IMU. The orientation of the devices will be compared. Measuring data from accelerometer and gyroscope provide orientation estimation in three dimensional space and for this purpose orientation in all three axes is needed. Accelerometer measures acceleration and gyroscope measures angular velocity. Orientation can be calculated by using one sensor, but both are affected by negative parameters which make estimation imprecise. Accelerometers measure all forces acting on it including gravitation. This fact can be used to estimate orientation, however, output data of accelerometer are quite noisy. Another possibility how to obtain orientation estimate is integration of gyroscopes data, but this estimation is insufficient due to bias. Combination of output data from both sensors, more precise orientation estimation can be obtained. Combination of sensors is called sensor fusion and is done by using Complementary filter based on Euler angles.

[1]  Xie Ling,et al.  Applications of zero-velocity detector and Kalman filter in zero velocity update for inertial navigation system , 2014, Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference.

[2]  Zhang Xiao-dong,et al.  A new zero velocity update algorithm for the shoe-mounted personal navigation system based on IMU , 2015, 2015 34th Chinese Control Conference (CCC).

[3]  Mohammad Zulkernine,et al.  An Empirical Evaluation of Web-Based Fingerprinting , 2015, IEEE Software.

[4]  J. D. Powell,et al.  Single baseline GPS based attitude heading reference system (AHRS) for aircraft applications , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[5]  Vojtech Simak,et al.  Ergonomic remote control of the mobile platform by inertial measurement of the hand movement , 2016, 2016 ELEKTRO.

[6]  Hojung Cha,et al.  LifeMap: A Smartphone-Based Context Provider for Location-Based Services , 2011, IEEE Pervasive Computing.

[7]  Aboelmagd Noureldin,et al.  Enhanced mobile robot outdoor localization using INS/GPS integration , 2009, 2009 International Conference on Computer Engineering & Systems.

[8]  Youngnam Han,et al.  Improved heading estimation for smartphone-based indoor positioning systems , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[9]  Jochen Schiller,et al.  Location Based Services , 2004 .

[10]  Ig-Jae Kim,et al.  Indoor location sensing using geo-magnetism , 2011, MobiSys '11.

[11]  Youngnam Han,et al.  SmartPDR: Smartphone-Based Pedestrian Dead Reckoning for Indoor Localization , 2015, IEEE Sensors Journal.

[12]  Paul D. Groves,et al.  Principles of GNSS, Inertial, and Multi-sensor Integrated Navigation Systems , 2012 .

[13]  W. Rosenstiel,et al.  SBIL: Scalable Indoor Localization and Navigation Service , 2007, 2007 Third International Conference on Wireless Communication and Sensor Networks.

[14]  Dongkai Yang,et al.  An enhanced technique for indoor navigation system based on WIFI-RSSI , 2015, 2015 Seventh International Conference on Ubiquitous and Future Networks.

[15]  Michal R. Nowicki,et al.  Simplicity or flexibility? Complementary Filter vs. EKF for orientation estimation on mobile devices , 2015, 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF).

[16]  James Aweya,et al.  Performance evaluation of CIR based location fingerprinting , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[17]  Akira Nakamura,et al.  Navigation system using ZigBee wireless sensor network for parking , 2012, 2012 12th International Conference on ITS Telecommunications.

[18]  Shervin Shahidi,et al.  GIPSy: Geomagnetic indoor positioning system for smartphones , 2015, 2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN).