Bayesian methodsBayesian / computational
鲁棒卡尔曼滤波器 (Robust Kalman Filter)
鲁棒卡尔曼滤波器是经典卡尔曼滤波器的扩展，旨在在观测值或过程噪声偏离高斯假设时，尤其是在数据包含异常值、重尾分布或 gross errors 时，仍能保持可靠的状态估计。通过用影响受限或基于 M-估计的修正替换或降低标准最小二乘更新的权重，它可以防止单个异常测量扭曲整个状态估计。
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来源
- Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. Journal of Basic Engineering, 82(1), 35-45. DOI: 10.1115/1.3662552 ↗
- Huber, P. J. & Ronchetti, E. M. (2011). Robust Statistics (2nd ed.). Wiley. ISBN: 978-0470129906
如何引用本页
ScholarGate. (2026, June 3). Robust Kalman Filter. ScholarGate. https://scholargate.app/zh/bayesian/robust-kalman-filter
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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