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基于粒子濾波算法的汽車狀態(tài)估計技術(shù)
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國家自然科學(xué)基金資助項目（10902049）,、國家高技術(shù)研究發(fā)展計劃(863計劃)資助項目(2008AA11A140)和南航引進人才科研基金資助項目（S0915-022）


Vehicle States Estimation Technology Based on Particle Filter Algorithm
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    摘要:

    將粒子濾波（particle filter, PF）算法應(yīng)用到汽車的狀態(tài)估計之中,，建立了包含定常統(tǒng)計特性噪聲和非線性輪胎的汽車動力學(xué)模型，根據(jù)汽車非線性狀態(tài)轉(zhuǎn)移函數(shù)完成對粒子的預(yù)測，基于當(dāng)前時刻的量測值實現(xiàn)對預(yù)測粒子權(quán)重的評估,，最后通過重采樣完成對汽車關(guān)鍵狀態(tài)量估計,。將PF估計器與常見的EKF,、UKF估計器進行了比較分析,，基于ADAMS/Car的虛擬試驗和實車試驗驗證了PF在汽車狀態(tài)估計中的可行性。

    Abstract:

    Particle filter (PF) algorithm was used in vehicle states estimation. A vehicle dynamics system containing constant noise and nonlinear tire model was established. First, the particles were predicted through nonlinear state transition function; then the weights of the predicted particles were evaluated based on current measurements. Finally, the key states were estimated though resample step. The PF estimator was compared with other estimators based on extended Kalman filter (EKF) and unscented Kalman filter (UKF). The results of virtual experiment based on ADAMS/Car and real vehicle experiment demonstrated that PF was available in vehicle states estimation.

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林 棻,趙又群,徐朔南.基于粒子濾波算法的汽車狀態(tài)估計技術(shù)[J].農(nóng)業(yè)機械學(xué)報,2011,42(2):23-27,22. Lin Fen, Zhao Youqun, Xu Shuonan. Vehicle States Estimation Technology Based on Particle Filter Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2011,42(2):23-27,22.

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