自适应算法在捷联惯导初始对准中的应用

Application of Adaptive Filtering Algorithm to Initial Alignment of Strapdown Inertial System

针对传统的卡尔曼滤波在捷联惯导初始对准中由于系统噪声和量测噪声方差阵未知时,滤波的精度和快速性不能达到要求,甚至导致发散的问题。提出了一种改进的Sage_Husa自适应滤波新算法,建立了捷联惯导系统初始对准误差模型,并在对捷联惯导系统误差模型进行简化的基础上,利用所设计的算法进行了仿真研究。仿真结果表明,改进的滤波算法使对准过程所需时间大大缩短,具有跟踪能力强、稳定性好和精确性高等特点,验证了该方法的有效性和正确性。

When the noise and noise measurement matrix are unknown in SINS initial alignment, the filtering accuracy and speed of the tradition Kalman fliter can not meet the requirement, or even divergence easily. Considering above reasons, in this paper, a novel Sage _ Husa adaptive filtering algorithm is proposed. Meanwhile, the error model of SINS initial alignment error model is established and simplified. Eventually, based on the simplified model ,we use the proposed algorithm to simulate. The simulation results show that the speed of process is inereasded sharply, and also good stability and high accuracy are guaranteed. In addition, simulation results are provided to demonstrate the effectiveness and correctness of the proposed method.