A New Approach to Linear Filtering and Prediction Problems
TL;DR — The 1960 paper introducing the Kalman filter — the estimator that flew Apollo and now runs in everything.
R. E. Kálmán, Research Institute for Advanced Study, Baltimore. “The classical filtering and prediction problem is re-examined using the Bode-Shannon representation…”
Twelve pages introducing what became the Kalman filter: a recursive estimator that fuses a noisy measurement with a model prediction, optimally, without storing the past.
Among the most-implemented algorithms ever published. It guided Apollo, and it is now inside GPS receivers, phone sensor fusion, robotics, finance and tracking of every kind. A genuinely rare case of a single paper becoming permanent infrastructure.
Where this came from
12 pages. A copy is archived locally against link rot; the header links the original source.