Abstract
The Kalman filter is a very useful algorithm for linear Gaussian estimation problems. It is extremely popular and robust in practical applications. The algorithm is easy to code and test. There are many reasons for the popularity of the Kalman filter in the real world, including stability and generality and simplicity. Moreover, the real-time computational complexity is very reasonable for high-dimensional problems. In particular, the computational complexity scales as the cube of the dimension of the state vector.
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© 2014 Springer-Verlag London
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Daum, F.E. (2014). Kalman Filters. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_61-2
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DOI: https://doi.org/10.1007/978-1-4471-5102-9_61-2
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