SR-CH∞KF用于弹丸飞行姿态测量研究

Research on SR-CH∞KF for projectile attitude measurement

为提高弹丸姿态测量精度,提出一种基于H∞滤波的平方根容积卡尔曼滤波。该方法通过三轴地磁传感器和陀螺仪组合测量模型,采用欧拉角算法模型减少状态维数并使状态方程呈现线性化,可以减少计算量。该方法可以适用于量测噪声不确定的情况,引入新息序列不断修正误差限定参数来更新量测噪声估计值,可以提高滤波的精度和鲁棒性。奇异值分解能够保证误差协方差矩阵的正定性,平方根形式能够提高容积卡尔曼滤波的数值稳定性和鲁棒性。利用地磁传感器与陀螺仪组合测量弹丸姿态的仿真实验来验证算法有效性,并与容积卡尔曼滤波和平方根容积卡尔曼滤波的效果进行对比,证明了所提算法的有效性与优越性。

A novel H∞ filter called square-root cubature H∞ Kalman filter is proposed for attitude measurement of high-spinning aircraft. In this method, a combined measurement model of three-axis geomagnetic sensor and gyroscope is used, and the Euler angle algorithm model is used to reduce the state dimension and linearize the state equation, which can reduce the amount of calculation. Differently the method can be applied to the case of measurement noise uncertainty. The innovation sequence is introduced to continuously modify the error limiting parameters to update the measurement noise estimation, which can improve the accuracy and robustness of filtering. The square root form can improve the numerical stability and robustness of cubature Kalman filter because orthogonal decomposition(QR) can ensure the positive definite of error covariance matrix. The algorithm is applied to the simulation experiment of projectile attitude measurement with the combination of geomagnetic sensor and gyroscope. The comparison with cubature Kalman filter and square-root cubature Kalman filter shows the effectiveness and superiority of the algorithm.