Electronics Optics & Control, Volume. 20, Issue 11, 105(2013)
An Improved Extend Kalman Filtering Algorithm Based on Asymptotic Stationary Process
In multitarget trackingthe measurement noise is not an absolute Gaussian distribution because of clutter and the undulation of RCS.A model of noise was studied based on asymptotic stationary processand a confidence function was introduced.A method that could feed back the confidence degree of the measured value to the filtering process was proposed.By correcting the gain matrix and covariance matrixthe effect of measuring noise fluctuation on filtering was reduced.The method could enhance the ability of the noise compression and restrain the peak error.Simulation result verifies the validity and feasibility of the method.
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[in Chinese], [in Chinese], [in Chinese]. An Improved Extend Kalman Filtering Algorithm Based on Asymptotic Stationary Process[J]. Electronics Optics & Control, 2013, 20(11): 105
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Received: Dec. 19, 2012
Accepted: --
Published Online: Dec. 4, 2013
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