【摘要】：提出了一種改進(jìn)型自適應(yīng)無(wú)跡卡爾曼濾波姿態(tài)算法,能夠有效的解決MEMS陀螺儀的漂移和噪聲問(wèn)題,同時(shí)減小運(yùn)動(dòng)加速度對(duì)加速度計(jì)的影響。將改進(jìn)的自適應(yīng)Sage-Husa算法與無(wú)跡卡爾曼濾波器相結(jié)合,使量測(cè)噪聲統(tǒng)計(jì)特性在線更新,提高系統(tǒng)的抗干擾能力,避免擴(kuò)展卡爾曼濾波的線性化誤差,可以得到精確的全姿態(tài)角。每次迭代只更新3個(gè)歐拉角,提高了系統(tǒng)的解算速度。飛行實(shí)驗(yàn)和分析表明:改進(jìn)算法能夠有效的提高姿態(tài)解算精度,收斂速度快,自適應(yīng)能力強(qiáng),穩(wěn)定可靠,具有較強(qiáng)的魯棒性,在干擾消失時(shí)能夠快速得到準(zhǔn)確姿態(tài)角。
[Abstract]:An improved adaptive unscented Kalman filter attitude algorithm is proposed, which can effectively solve the drift and noise problems of MEMS gyroscopes and reduce the effect of motion acceleration on accelerometers. By combining the improved adaptive Sage-Husa algorithm with the unscented Kalman filter, the statistical characteristics of the measurement noise can be updated online, the anti-jamming ability of the system can be improved, and the linearization error of the extended Kalman filter can be avoided, and the accurate attitude angle can be obtained. Only three Euler angles are updated in each iteration, which improves the solution speed of the system. Flight experiments and analysis show that the improved algorithm can effectively improve the accuracy of attitude resolution, fast convergence speed, strong adaptive ability, stable and reliable, strong robustness, and can quickly get accurate attitude angle when the interference disappears.
【作者單位】： 太原理工大學(xué)物理與光電工程學(xué)院;太原理工大學(xué)信息工程學(xué)院;
【基金】：山西省自然科學(xué)基金項(xiàng)目(2015011050)
【分類號(hào)】：TN713;V249;V279

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