UKF滤波器性能分析及其在轨道计算中的仿真试验

Unscented Kalman Filter for Non-linear Estimation

讨论了UT(unscented transform)变换的性质,给出了一种新的扩展型卡尔曼滤波器UKF(unscentedKalman filter),它不仅具有较高的精度,而且不必计算偏导数阵。仿真分析的结果表明,UKF有良好的状态估计性能,使用简便,适合于非线性系统状态估计。

The extended Kalman filter is one of the most widely used methods for tracking and estimation of non linear systems through linearizing non-linear models. In recent several decades people have realized that there are a lot of constraints in application of the EKF for its hard implementation and intractability. In this paper a new estimation method is pro posed, which takes advantage of the Unscented Transformation method thus approximating the true mean and variance more accurately. The new method can be applied to nonlinear systems without the linearization process necessary for the EKF, and it does not demand a Gaussian distribution of noise and what＇s more, its ease of implementation and more accurate estimation features enables it to demonstrate its good performance in numerical experiments of satellite orbit simulation.