Evaluation of derivative free Kalman filter and fusion in non-linear estimation

Kashyap, SK and Raol, JR (2006) Evaluation of derivative free Kalman filter and fusion in non-linear estimation. In: IEEE CCECE/CCGEI, May 2006, Ottawa.

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In recent literature a derivative free Kalman filter (DFKF) a method that propagates mean and covariance using non-linear transformation is frequently used. In this paper i) factorised 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 weight is carried out. DFKF is more accurate and easier to implement. A data fusion scheme is involved. 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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: xA9;2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Uncontrolled Keywords: Non-linear systems;Target tracking;Kalman filtering;Derivative free transformation and Kalman filter;Data fusion;Parameter estimation
Subjects: AERONAUTICS > Aircraft Stability and Control
Depositing User: M/S ICAST NAL
Date Deposited: 22 Feb 2008
Last Modified: 17 Jun 2010 04:53
URI: http://nal-ir.nal.res.in/id/eprint/4591

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