Title
Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field.
Abstract
Pedestrian navigation systems (PNS) using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs) to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF). This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1) walking along straight paths; (2) standing still for a long time. It is observed that these motion constraints (called virtual sensor), though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth's magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD) and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms.
Year
DOI
Venue
2016
10.3390/s16091455
SENSORS
Keywords
Field
DocType
pedestrian navigation system,drift reduction in INS,magnetic anomaly detection,multi-sensor fusion
Inertial frame of reference,Pedestrian,Magnetic field,Extended Kalman filter,Observable,Simulation,Control theory,Magnetometer,Electronic engineering,Inertial measurement unit,Engineering,Calibration
Journal
Volume
Issue
ISSN
16
9.0
1424-8220
Citations 
PageRank 
References 
5
0.51
4
Authors
4
Name
Order
Citations
PageRank
Muhammad Ilyas161.91
Kuk Cho282.95
Seung-Ho Baeg3205.98
Sangdeok Park46915.52