Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters

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ID: 120075
2018
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Abstract
An enhanced pedestrian dead reckoning (PDR) based navigation algorithm, which uses two cascaded Kalman filters (TCKF) for the estimation of course angle and navigation errors, is proposed. The proposed algorithm uses a foot-mounted inertial measurement unit (IMU), waist-mounted magnetic sensors, and a zero velocity update (ZUPT) based inertial navigation technique with TCKF. The first stage filter estimates the course angle error of a human, which is closely related to the heading error of the IMU. In order to obtain the course measurements, the filter uses magnetic sensors and a position-trace based course angle. For preventing magnetic disturbance from contaminating the estimation, the magnetic sensors are attached to the waistband. Because the course angle error is mainly due to the heading error of the IMU, and the characteristic error of the heading angle is highly dependent on that of the course angle, the estimated course angle error is used as a measurement for estimating the heading error in the second stage filter. At the second stage, an inertial navigation system-extended Kalman filter-ZUPT (INS-EKF-ZUPT) method is adopted. As the heading error is estimated directly by using course-angle error measurements, the estimation accuracy for the heading and yaw gyro bias can be enhanced, compared with the ZUPT-only case, which eventually enhances the position accuracy more efficiently. The performance enhancements are verified via experiments, and the way-point position error for the proposed method is compared with those for the ZUPT-only case and with other cases that use ZUPT and various types of magnetic heading measurements. The results show that the position errors are reduced by a maximum of 90% compared with the conventional ZUPT based PDR algorithms.
Reference Key
song2018sensorsenhanced Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jin Woo Song;Chan Gook Park;Song, Jin Woo;Park, Chan Gook;
Journal sensors
Year 2018
DOI
10.3390/s18041281
URL
https://www.mdpi.com/1424-8220/18/4/1281
Keywords
pedestrian dead reckoning zero velocity update course angle error two cascaded kalman filters (tckf) ins-ekf-zupt

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