方法证据记录
Kalman Filter
The Kalman filter is an optimal recursive algorithm for estimating the hidden state of a linear dynamical system from noisy measurements. At each time step it alternates between a prediction step — projecting the state forward using the system model — and an update step that corrects the prediction with the new observation, producing minimum-variance state estimates and their uncertainty in real time.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Kalman Filter (Linear-Gaussian State-Space Filter)
分类方法记录 · bayesian / bayesian
- 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
- Welch, G. & Bishop, G. (2006). An Introduction to the Kalman Filter. University of North Carolina at Chapel Hill, Technical Report TR 95-041. · URL
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