基于非线性映射的自适应混合Kalman/H∞滤波器

Kalman滤波器的精度高，但是鲁棒性差。H∞滤波器虽然鲁棒性好，但是精度不高，将两种滤波器进行混合获得新的滤波器可同时具备高精度和对干扰噪声的鲁棒性。通过对Kalman滤波器的实时性能评价，提出了一种基于非线性映射的自适应调节权值混合Kalman/H∞滤波器，并通过全球定位系统/推位组合导航模型对提出的方法进行了仿真验证。仿真结果表明，在干扰噪声统计特性变化和系统模型存在摄动条件下，与Kalman滤波和H∞滤波方法相比，所提出的混合Kalman/H∞滤波方法具有更高的滤波精度，更适用于实际应用。

Adaptive hybrid Kalman/H∞ filter based on nonlinear mapping

The precision of Kalman filter is high, but it is not robust to unknown disturbance. The robustness of H∞ filter is good, but the precision is low. Hybrid Kalman/H∞ filter can obtain both robustness to noise and high precision. By evaluating the performance of Kalman filter, an adaptive hybrid Kalman/H∞ filter based on nonlinear mapping is proposed. Simulations are performed based on global positioning system/dead reckoning integrated navigation model to confirm the performance of the proposed method. As can be seen from simulation results, when statistics of the noise change and system model perturbation exists, the precision of the proposed hybrid Kalman/H∞ filter is improved as compared with Kalman filter and H∞ filter， thus it is more suitable for practical applications.