A way of predicting what a system is going to do next when you don’t have exact information (like most real-world things).
Examples: smoothing GPS location data, altitude estimation
- Detailed breakdown and illustrations of the math behind Kalman filters
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Carveth Reed, a British logician and philosopher is attributed with the quote, “It is better to be vaguely right than exactly wrong” (sometimes attributed to the economist John Maynard Keynes). This is a useful idiom for a number of problems where information is limited or lacking precision.