Electronics Optics & Control, Volume. 20, Issue 11, 105(2013)

An Improved Extend Kalman Filtering Algorithm Based on Asymptotic Stationary Process

[in Chinese]... [in Chinese] and [in Chinese] |Show fewer author(s)
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    In multitarget trackingthe 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 processand 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 matrixthe 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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    Paper Information

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    Received: Dec. 19, 2012

    Accepted: --

    Published Online: Dec. 4, 2013

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2013.11.023

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