| Outlier Rejecting Multirate Model for State Estimation |
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| 作者姓名： | 肖艳军 李建勋 薛阳 |
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| 作者单位： | School of Electronic Information & Electrical Eng. Shanghai Jiaotong Univ. Shanghai 200030，China，School of Electronic Information & Electrical Eng. Shanghai Jiaotong Univ. Shanghai 200030，China，School of Electronic Information & Electrical Eng. Shanghai Jiaotong Univ. Shanghai 200030，China |
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| 基金项目： | NationalNaturalScienceFoundationofChina(60304007)andQMXProjectofShanghaiScienceandTechnologyDevelopmentFoun-dation(04QMX1410) |
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| 摘 要： | IntroductionMeasured data is often contaminated by noisein state estimation.Kalman filter is a powerfultool for signal extracting.It is especially efficientin estimating spatially inhomogeneous signal whenthe noise is Gaussian.Due to process noise or non-stationary environment,the measured data is usu-ally corrupted by outliers.The performance is de-graded seriously.Generally,there are two kinds ofapproaches to handle this problem.Outlier can bedetected based on renovation1],then be replace…
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Outlier Rejecting Multirate Model for State Estimation |
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| XIAO Yan-jun,LI Jian-xun,XUE Yang.Outlier Rejecting Multirate Model for State Estimation[J].Journal of Shanghai Jiaotong university,2006,11(1). |
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| Authors: | XIAO Yan-jun LI Jian-xun XUE Yang |
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| Abstract: | Wavelet transform was introduced to detect and eliminate outliers in time-frequency domain. The outlier rejection and multirate information extraction were initially incorporated by wavelet transform, a new outlier rejecting multirate model for state estimation was proposed. The model is applied to state estimation with interacting multiple model, as the outlier is eliminated and more reasonable multirate information is extracted, the estimation accuracy is greatly enhanced. The simulation results prove that the new model is robust to outliers and the estimation performance is significantly improved. |
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| Keywords: | wavelet transform outlier elimination multirate model |
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