Bayesian methodsBayesian / computational

Hierarchical Kalman Filter

The Hierarchical Kalman Filter (HKF) extends the classic Kalman filter to systems with multiple levels or scales of state representation. It applies Kalman recursions at each level of a hierarchy — from coarse to fine resolution or from global to local subsystems — and passes information across levels via upward and downward sweeps, producing optimal linear state estimates throughout a structured state-space.

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Sources

  1. Chou, K. C., Willsky, A. S., & Benveniste, A. (1994). Multiscale recursive estimation, data fusion, and regularization. IEEE Transactions on Automatic Control, 39(3), 464–478. DOI: 10.1109/9.280748
  2. Sarkka, S. (2013). Bayesian Filtering and Smoothing. Cambridge University Press. ISBN: 978-1107619289

Related methods

ScholarGateHierarchical Kalman Filter (Hierarchical Kalman Filter). Retrieved 2026-06-04 from https://scholargate.app/en/bayesian/hierarchical-kalman-filter