Orientation Estimation for Sensor Motion Tracking Using Interacting Multiple Model Filter

Chin-Der WANN
Jian-Hau GAO

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E93-A    No.8    pp.1565-1568
Publication Date: 2010/08/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E93.A.1565
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Systems and Control
motion tracking,  interacting multiple model,  Kalman filtering,  orientation estimation,  quaternion,  

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In this letter, we present a real-time orientation estimation and motion tracking scheme using interacting multiple model (IMM) based Kalman filtering method. Two nonlinear filters, quaternion-based extended Kalman filter (QBEKF) and gyroscope-based extended Kalman filter (GBEKF) are utilized in the proposed IMM-based orientation estimator for sensor motion state estimation. In the QBEKF, measurements from gyroscope, accelerometer and magnetometer are processed; while in the GBEKF, sole measurements from gyroscope are processed. The interacting multiple model algorithm is used for fusing the estimated states via adaptive model weighting. Simulation results validate the proposed design concept, and the scheme is capable of reducing overall estimation errors in sensor motion tracking.