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基于粒子濾波算法的汽車(chē)狀態(tài)估計(jì)技術(shù)
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國(guó)家自然科學(xué)基金資助項(xiàng)目（10902049）、國(guó)家高技術(shù)研究發(fā)展計(jì)劃(863計(jì)劃)資助項(xiàng)目(2008AA11A140)和南航引進(jìn)人才科研基金資助項(xiàng)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(chē)的狀態(tài)估計(jì)之中，建立了包含定常統(tǒng)計(jì)特性噪聲和非線性輪胎的汽車(chē)動(dòng)力學(xué)模型，根據(jù)汽車(chē)非線性狀態(tài)轉(zhuǎn)移函數(shù)完成對(duì)粒子的預(yù)測(cè)，基于當(dāng)前時(shí)刻的量測(cè)值實(shí)現(xiàn)對(duì)預(yù)測(cè)粒子權(quán)重的評(píng)估，最后通過(guò)重采樣完成對(duì)汽車(chē)關(guān)鍵狀態(tài)量估計(jì)。將PF估計(jì)器與常見(jiàn)的EKF、UKF估計(jì)器進(jìn)行了比較分析，基于ADAMS/Car的虛擬試驗(yàn)和實(shí)車(chē)試驗(yàn)驗(yàn)證了PF在汽車(chē)狀態(tài)估計(jì)中的可行性。

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    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(chē)狀態(tài)估計(jì)技術(shù)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),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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