本文選題：姿態(tài)估計(jì)　切入點(diǎn)：加速度補(bǔ)償　出處：《電子技術(shù)應(yīng)用》2017年04期 　論文類型：期刊論文

【摘要】：設(shè)計(jì)了一種基于模糊規(guī)則調(diào)整的串級(jí)線性卡爾曼(LKF)姿態(tài)解算方法,用旋轉(zhuǎn)矩陣部分元素建立狀態(tài)方程首先以機(jī)動(dòng)加速度補(bǔ)償?shù)募铀俣葹橛^測(cè)量,并采用模糊規(guī)則調(diào)整不同運(yùn)動(dòng)狀態(tài)下的協(xié)方差陣,減小加速度的干擾,得到水平姿態(tài)角;然后采用磁強(qiáng)信息和姿態(tài)信息獲取間接觀測(cè)量,得到偏航角。動(dòng)靜態(tài)測(cè)試表明,該方法消除了累計(jì)誤差和磁干擾對(duì)水平傾角的耦合干擾,與擴(kuò)展卡爾曼濾波(EKF)相比,提高了在運(yùn)動(dòng)加速度干擾和磁場(chǎng)干擾下的姿態(tài)估計(jì)精度,并且降低了計(jì)算量。
[Abstract]:A cascade linear Kalman LKF attitude solution method based on fuzzy rule adjustment is designed. The state equation is established by using some elements of the rotation matrix. Firstly, the acceleration compensated by the maneuvering acceleration is taken as the observation quantity. The covariance matrix in different motion states is adjusted by fuzzy rules to reduce the disturbance of acceleration and the horizontal attitude angle is obtained, then the indirect observation is obtained by using magnetic intensity information and attitude information, and the yaw angle is obtained. Compared with the extended Kalman filter (EKF), this method can improve the precision of attitude estimation under the disturbance of moving acceleration and magnetic field, and reduce the computational complexity. The proposed method eliminates the coupling interference of accumulated error and magnetic disturbance to horizontal inclination angle, and improves the precision of attitude estimation under the disturbance of moving acceleration and magnetic field, compared with the extended Kalman filter (EKF).
【作者單位】： 華東理工大學(xué)信息科學(xué)與工程學(xué)院;
【分類號(hào)】：TP212;TN713
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本文編號(hào)：1556801