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
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摘要: 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。Abstract: 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 proposed,which takes advantage of the Unscented Transformation method thus approximating the true mean and variance more accurately.The new method can be applied to non-linear 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.