摘要
在GPS/AHRS(航姿参考系统)组合导航的数据融合中,常规UKF在应用中由于计算误差易导致协方差负定,影响滤波的精度,甚至使滤波发散而导致系统无法正常工作.针对这一问题提出了一种改进的自适应SRUKF算法,不仅能够解决协方差负定带来的系统无法正常工作的问题,而且能够在保证精度的同时降低系统的计算量.仿真数据结果表明,在先验噪声未知并且噪声时变的情况下,改进的自适应SRUKF算法能够提高系统的精度和稳定性.
In the data fusion of tightly errors of traditional UKF resulted in a coupled GPS/Attitude Heading Reference negative definite state of covariance. The System （AHRS）, the calculation results may uhimately reduce the accuracy of filter and even cause divergence of filters which lead to abnormality of the system. An improved adaptive SRUKF （square root unsensitive Kalman filter） provided in this paper, can help solve the problem of negative definite state covariance and lower calculation complexity. The filtering results of the simulation data show that, under the condition of unknown and real-time system noise statistics, the improved adaptive SRUKF in a tightly coupled integrated navigation system have better performance both in accuracy and in robustness.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2012年第10期1300-1303,共4页
Journal of Harbin Engineering University
基金
国家863计划基金资助项目(2009AA12Z314)
