Title :
Evaluation of Derivative Free Kalman Filter and Fusion in Non-Linear Estimation
Author :
Kashyap, S.K. ; Raol, J.R.
Author_Institution :
Flight Mech. & Control Div., Nat. Aerosp. Lab., Bangalore
Abstract :
In recent literature a derivative free Kalman filter (DFKF) a method that propagates mean and covariance using nonlinear transformation is frequently used. In this paper i) factorized version of EKF (UD extended Kalman filter or UDEKF) and ii) DFKF are studied and evaluated using various sets of simulated data of the non-linear systems. Sensitivity study of DFKF with respect to tuning parameters used in creation of sigma points and the associated weights is carried out. DFKF is more accurate and easier to implement. A data fusion scheme is evolved and presented based on DFKF for similar sensors. Its performance is evaluated. It is observed that fusion enhances the estimation accuracy of the state of non-linear plant. Application of DFKF to non-linear parameter estimation problem is also demonstrated
Keywords :
Kalman filters; nonlinear systems; parameter estimation; sensor fusion; data fusion scheme; derivative free Kalman filter; factorized EKF version; nonlinear parameter estimation problem; nonlinear systems; nonlinear transformation; Aerospace control; Aircraft; Kinematics; Laboratories; Noise generators; Nonlinear control systems; Parameter estimation; Random variables; Sensor fusion; State estimation; Data fusion; Derivative free transformation and Kalman filter; Kalman filtering; Non-linear systems; Parameter estimation; Target tracking;
Conference_Titel :
Electrical and Computer Engineering, 2006. CCECE '06. Canadian Conference on
Conference_Location :
Ottawa, Ont.
Print_ISBN :
1-4244-0038-4
Electronic_ISBN :
1-4244-0038-4
DOI :
10.1109/CCECE.2006.277406
