z-logo
open-access-imgOpen Access
Orientation and Displacement Detection for Smartphone Device Based IMUs
Author(s) -
Abhijit Suprem,
Vishal Deep,
Tarek Elarabi
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2016.2631000
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Commonly, navigation uses global positioning system/network (GPS) signals to determine location. In addition, GPS data can be collected over time to determine the path taken. In spite of the ubiquity of GPS signals on the earth's surface, there are certain locations where GPS signals are not available, such as inside buildings or tunnels. Therefore, to determine accurate positioning in areas where the GPS signals are unavailable, an inertial measurement unit (IMU) can be used in conjunction with the GPS data. Modern IMUs are small enough to be contained in Microelectromechanical systems (MEMS) chips, including smartphone devices, such as iPhones. This paper studies the integration between the GPS signal and the collected data from smartphones' MEMS sensors. It also investigates the possibility of using the integrated GPS/MEMS information to estimate route when the GPS signal is missing. We propose estimating the missing GPS signal by sensor integration of smartphone data. This paper would enhance the GPS navigation to determine exact positions even in the case of signal failures. Modern IMUs are expensive, and this paper shows that GPS/IMU integration can be accomplished with off-the-shelf navigational components. This paper proposes a novel technique for estimating the missing GPS route by integrating data from the sensors available in modern smartphones.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom