| Two-step measurement update for extended Kalman filtering |
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| 作者姓名： | Zhang Yong'an Zhou Di & Duan GuangrenCenter for Control and Guidance Harbin Institute of Technology Harbin P. R. China |
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| 作者单位： | Zhang Yong'an，Zhou Di & Duan GuangrenCenter for Control and Guidance，Harbin Institute of Technology，Harbin 150001，P. R. China |
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| 基金项目： | ThisprojectwassupportedbytheNationalNaturalScienceFoundationofChina(60104003，60374204). |
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| 摘 要： | 1.INTRODUCTION TheextendedKalmanfilter(EKF)isthemost widelyusednonlinearfilterbecauseofitssimplicity despiteitsinconsistenceinsomeapplications.Thein consistenceoftheEKFmainlyarisesfromtheuseof linearization.Sincethereferencepointsforthelin earizationarearoundthepriorestimatesofthestate (filteredestimateforlinearizationofstatetransition equationandpredictiveestimateforlinearizationof measurementequation,respectively),agoodprior estimateisveryimportantfortheEKF.Inmanycas es,themeasur…
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Two-step measurement update for extended Kalman filtering |
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| Zhang Yong''''an,Zhou Di & Duan GuangrenCenter for Control and Guidance,Harbin Institute of Technology,Harbin ,P. R. China.Two-step measurement update for extended Kalman filtering[J].Journal of Systems Engineering and Electronics,2005,16(1). |
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| Authors: | Zhang Yong'an Zhou Di Duan Guangren |
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| Institution: | Center for Control and Guidance, Harbin Institute of Technology, Harbin 150001, P. R. China |
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| Abstract: | The nonlinear filtering for a class of discrete-time stochastic dynamic systems whose measurement equations contain linear (or universal linearizable) components and nonlinear components which are mutually statistical independent is investigated. A two-step measurement update is proposed for the filtering of the systems. The first-step update is a linear (or universal linearization) measurement correction which introduces an intermediate estimate, while the second-step nonlinear linearization update produces the final posterior estimate based on the first-step estimate. Since the first measurement correction is a linear or universal linearization update, it provides an accurate linearization reference point for the second nonlinear measurement update. Two simulation examples show superiority of the new estimation method. |
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| Keywords: | universal linearization extended Kalman filter modified gain extended Kalman filter target tracking |
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