改进型自适应无迹卡尔曼姿态算法
发布时间：2018-10-14 21:09
【摘要】：提出了一种改进型自适应无迹卡尔曼滤波姿态算法,能够有效的解决MEMS陀螺仪的漂移和噪声问题,同时减小运动加速度对加速度计的影响。将改进的自适应Sage-Husa算法与无迹卡尔曼滤波器相结合,使量测噪声统计特性在线更新,提高系统的抗干扰能力,避免扩展卡尔曼滤波的线性化误差,可以得到精确的全姿态角。每次迭代只更新3个欧拉角,提高了系统的解算速度。飞行实验和分析表明:改进算法能够有效的提高姿态解算精度,收敛速度快,自适应能力强,稳定可靠,具有较强的鲁棒性,在干扰消失时能够快速得到准确姿态角。
[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.
【作者单位】： 太原理工大学物理与光电工程学院;太原理工大学信息工程学院;
【基金】：山西省自然科学基金项目(2015011050)
【分类号】：TN713;V249;V279
本文编号：2271650
[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.
【作者单位】： 太原理工大学物理与光电工程学院;太原理工大学信息工程学院;
【基金】：山西省自然科学基金项目(2015011050)
【分类号】：TN713;V249;V279
【相似文献】
相关期刊论文 前2条
1 傅惠民;娄泰山;吴云章;;无迹增量滤波方法[J];航空动力学报;2012年07期
2 林国语;贾云献;孙磊;;基于无迹卡尔曼滤波的直升机主减速器剩余安全寿命预测[J];机械传动;2014年05期
，本文编号：2271650
本文链接：https://www.wllwen.com/kejilunwen/dianzigongchenglunwen/2271650.html
