一种用于非线性系统的自适应两步滤波器设计

Cao Jian, Zhuang Xiaoping
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引用次数: 1

摘要

两步过滤器是定义一组新状态参数的过滤器。这些状态参数是反映系统实时状态的非线性函数。然后,利用卡尔曼滤波获取最佳估计值,利用高斯-牛顿交替算法计算出最佳答案。在不知道实际噪声统计值的情况下,应将可变噪声统计估计器与两步滤波相结合。应用这种方法称为自适应非线性滤波。分析了自适应两步滤波器的仿真结果,得出自适应两步滤波器的性能优于其他滤波器的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Design on Adaptive Two-Step Filter Applied in Nonlinear System
Two-step filter is a filter that defines a set of new state parameters. These state parameters are nonlinear functions reflecting real-time states of system. Then, applying Kalman filter to acquire best estimate value, we can calculate best answer by Gauss-Newton alternate arithmetic. Not knowing real noise statistic values, we should combine variable noise statistic estimator with two-step filter. Applying this method is called adaptive nonlinear filter. Analyzing simulation results of adaptive two-step filter, it is concluded that performance of adaptive two-step filter exceeds one of other filters.
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