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concepts/kalman-filter.md
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concepts/kalman-filter.md
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title: "Kalman 滤波"
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created: 2026-06-22
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updated: 2026-06-22
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type: concept
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tags: [state-estimation, filtering, linear-systems]
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sources: [nano-filter]
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---
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# Kalman 滤波
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Kalman filter (KF) 是线性高斯系统下 [[bayesian-filtering|贝叶斯滤波]]的精确解析解。利用高斯分布在**线性变换下的封闭性**和**条件化下的共轭性**,KF 递归地更新均值和协方差矩阵。
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## 基本形式
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对于系统 $x_t = A x_{t-1} + \xi_{t-1}$,$y_t = C x_t + \zeta_t$(噪声均为零均值高斯):
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- 预测步:
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- $\hat{x}_{t|t-1} = A \hat{x}_{t-1|t-1}$
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- $P_{t|t-1} = A P_{t-1|t-1} A^\top + Q$
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- 更新步(Kalman gain $K_t = P_{t|t-1} C^\top (C P_{t|t-1} C^\top + R)^{-1}$):
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- $\hat{x}_{t|t} = \hat{x}_{t|t-1} + K_t (y_t - C \hat{x}_{t|t-1})$
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- $P_{t|t} = (I - K_t C) P_{t|t-1}$
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## 非线性扩展
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对非线性系统,KF 的封闭性不再成立,衍生出:
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- [[extended-kalman-filter|EKF]] — Taylor 线性化
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- [[unscented-kalman-filter|UKF]] — 无迹变换
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- [[nano-filter|NANO]] — 自然梯度优化
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## 参考
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- [[bayesian-filtering|Bayesian Filtering]]
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- [[gaussian-filtering|Gaussian Filtering]]
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- [[nano-filter|NANO Filter]]
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