无迹增量滤波方法

傅惠民; 娄泰山; 吴云章

无迹增量滤波方法

北京航空航天大学小样本技术研究中心,北京 100191

基金项目: 国家重点基础研究发展计划(2012CB720000)

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出版历程
- 收稿日期: 2012-02-15
- 刊出日期: 2012-07-28

Unscented incremental filter method

Research Center of Small Sample Technology, Beijing University of Aeronautics and Astronautics,Beijing 100191,China

摘要

摘要: 提出无迹增量滤波(UIF)的概念,建立一般无迹增量滤波模型及其分析方法,并对具有加性噪声的无迹增量滤波进行了详细讨论,给出其递推算法.在工程实际中,由于环境因素的影响、测量设备的不稳定性、模型和参数的选取不当等原因往往带来未知的系统误差.在这种情况下,传统的无迹Kalman滤波方法(UKF)在递推过程中会产生较大误差,甚至导致发散.提出的无迹增量滤波方法能够成功消除这种未知的系统误差,提高滤波的精度.该方法计算简单,便于工程应用.
- 无迹增量滤波 /
- 无迹Kalman滤波 /
- 增量量测方程 /
- 系统误差 /
- 滤波精度 /
- 深空探测
Abstract: The unscented incremental filter(UIF)model and analysis method were put forward, in which its concept, basis equations and the recursive calculative steps were established, and special concern was given to UIF with additive noise. In practice, the measurement data have unknown system errors, for the environmental factors, the instability of measurement equipments and the improper models and parameters. Under these conditions, the classic unscented Kalman filter(UKF)have greater filtering error, and even lead to diverge. The presented UIF can successfully eliminate these unknown system errors and improve the filtering accuracy. The method is simple to calculate and easy to apply in engineering.
- unscented incremental filter(UIF) /
- unscented Kalman filter(UKF) /
- incremental measurement equation /
- system error /
- filtering accuracy /
- deep space exploration

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参考文献(14)

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