Open AccessDe‐noising MEMS inertial sensors for low‐cost vehicular attitude estimation based on singular spectrum analysis and independent component analysis
Author(s) -
Wu Z.W.,
Yao M.L.,
Ma H.G.,
Jia W.M.
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2013.0422
Subject(s) - accelerometer , noise (video) , acceleration , gyroscope , control theory (sociology) , vibration , independent component analysis , inertial navigation system , singular spectrum analysis , inertial measurement unit , inertial frame of reference , microelectromechanical systems , component (thermodynamics) , computer science , engineering , acoustics , artificial intelligence , physics , aerospace engineering , singular value decomposition , control (management) , classical mechanics , quantum mechanics , image (mathematics) , thermodynamics , operating system
A novel method to de‐noise microelectromechanical system (MEMS) inertial sensors by cascaded integration of singular spectrum analysis (SSA) and independent component analysis (ICA) is proposed to improve the attitude accuracy for low‐cost attitude estimation. The low‐frequency vibration noise and acceleration disturbance induce large errors to attitude estimation since MEMS accelerometers provide attitude measurement for sensor fusion by measuring the gravity vector. It is proposed to remove the low‐frequency vibration noise by SSA and to mitigate the acceleration disturbance by ICA. SSA can effectively separate the trend and periodic vibration noise and ICA can effectively extract the acceleration disturbance with the help of turning rate measured by the yaw gyro. The proposed technique was tested on real road experiments showing significant improvement of attitude accuracy.