TY - GEN
T1 - A MEMS multi-sensors system for pedestrian navigation
AU - Zhuang, Yuan
AU - Chang, Hsiu Wen
AU - El-Sheimy, Naser
N1 - Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Micro-electro-mechanical system (MEMS) sensors are widely used in many applications due to their low cost, low power consumption, small size and light weight. Such MEMS sensors which are usually called multi-sensors include accelerometers, gyroscopes, magnetometers and barometers. In this research, Samsung Galaxy Note is used as the MEMS multi-sensors platform for pedestrian navigation. It contains a three-axis accelerometer, a three-axis gyroscope, a three-axis magnetometer and GPS receiver. Pedestrian Dead Reckoning (PDR) algorithms which include step detection, stride length estimation, heading estimation and PDR mechanization are carefully discussed in this paper. GPS solution is the major aiding source to reduce the MEMS IMU position, velocity and attitude errors when GPS signals are available. Magnetometers are also used to reduce the attitude errors of gyroscopes if there are no environment disturbances. A loosely-coupled extended Kalman Filter is implemented in the paper to fuse all the information to obtain the position result. Two typical scenarios are tested and analyzed in this paper: walking from outdoor to indoor and indoor walking. The MEMS multi-sensors system works well for both scenarios. To conclude, algorithms of MEMS multi-sensors system can provide an accurate, reliable and continuous result for pedestrian navigation on the platform of smart phone.
AB - Micro-electro-mechanical system (MEMS) sensors are widely used in many applications due to their low cost, low power consumption, small size and light weight. Such MEMS sensors which are usually called multi-sensors include accelerometers, gyroscopes, magnetometers and barometers. In this research, Samsung Galaxy Note is used as the MEMS multi-sensors platform for pedestrian navigation. It contains a three-axis accelerometer, a three-axis gyroscope, a three-axis magnetometer and GPS receiver. Pedestrian Dead Reckoning (PDR) algorithms which include step detection, stride length estimation, heading estimation and PDR mechanization are carefully discussed in this paper. GPS solution is the major aiding source to reduce the MEMS IMU position, velocity and attitude errors when GPS signals are available. Magnetometers are also used to reduce the attitude errors of gyroscopes if there are no environment disturbances. A loosely-coupled extended Kalman Filter is implemented in the paper to fuse all the information to obtain the position result. Two typical scenarios are tested and analyzed in this paper: walking from outdoor to indoor and indoor walking. The MEMS multi-sensors system works well for both scenarios. To conclude, algorithms of MEMS multi-sensors system can provide an accurate, reliable and continuous result for pedestrian navigation on the platform of smart phone.
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U2 - 10.1007/978-3-642-37407-4_60
DO - 10.1007/978-3-642-37407-4_60
M3 - Conference contribution
AN - SCOPUS:84880750359
SN - 9783642374067
T3 - Lecture Notes in Electrical Engineering
SP - 651
EP - 660
BT - China Satellite Navigation Conference, CSNC 2013 - Proceedings
PB - Springer Verlag
T2 - 4th China Satellite Navigation Conference, CSNC 2013
Y2 - 13 May 2013 through 17 May 2013
ER -