【摘要】 针对捷联惯导初始对准问题,提出了一种具有干扰抑制能力的四元数自适应卡尔曼滤波初始对准算法。通过将初始对准问题转化为Wahba姿态确定问题,直接建立四元数的滤波模型,并采用自适应卡尔曼滤波对初始时刻姿态四元数进行估计,利用姿态四元数更新求出当前姿态来实时地反映载体的姿态变化。针对直接构建量测模型导致收敛速度慢的问题,提出一种基于最优四元数估计法构造K矩阵原理的改进算法。利用三轴转台模拟不同的摇摆环境进行实验,转台实验表明了改进算法具有较快的收敛速度和良好的稳定性及精度,中等精度的惯导系统在150s至200s的对准时间内,航向角均值误差小于2’。更多还原

【Abstract】 An anti-disturbance initial alignment algorithm with quaternion adaptive Kalman filter is presented for strap-down inertial navigation system(SINS). By transforming the problem of initial alignment into Wahba attitude determination, the measurement model with quaternion is built directly, and an adaptive Kalman filter is adopted to estimate the initial attitude quaternion. By using the updating of attitude quaternion, the body’s current attitude is obtained to reflect the attitude’s change in real time. In view that the direct-constructed measurement model has the problem of slow convergence, an improved quaternion adaptive Kalman filter is proposed, which is based on the principle of building K matrix with optimal quaternion method, which has. Experiments under different swing environment with three-axis turntable show that this algorithm has fast convergence speed, high stability and good precision. The mean headingerror of the medium-accuracy SINS is less than 2’ for alignment time from 150 s to 200s.更多还原