Least-squares estimation: from Gauss to Kalman
- 1 July 1970
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Spectrum
- Vol. 7 (7) , 63-68
- https://doi.org/10.1109/mspec.1970.5213471
Abstract
This discussion is directed to least-squares estimation theory, from its inception by Gauss1 to its modern form, as developed by Kalman.2 To aid in furnishing the desired perspective, the contributions and insights provided by Gauss are described and related to developments that have appeared more recently (that is, in the 20th century). In the author's opinion, it is enlightening to consider just how far (or how little) we have advanced since the initial developments and to recognize the truth in the saying that we ``stand on the shoulders of giants.''Keywords
This publication has 13 references indexed in Scilit:
- On the identification of variances and adaptive Kalman filteringIEEE Transactions on Automatic Control, 1970
- Adaptive filteringAutomatica, 1969
- Divergence in the Kalman filter.AIAA Journal, 1967
- Comment on "A Statistical Optimizing Navigation Procedure for Space Flight"AIAA Journal, 1963
- New Results in Linear Filtering and Prediction TheoryJournal of Basic Engineering, 1961
- A New Approach to Linear Filtering and Prediction ProblemsJournal of Basic Engineering, 1960
- Recursion formulas for growing memory digital filtersIEEE Transactions on Information Theory, 1958
- Stochastic Estimation of the Maximum of a Regression FunctionThe Annals of Mathematical Statistics, 1952
- A Stochastic Approximation MethodThe Annals of Mathematical Statistics, 1951
- An Extension of Wiener's Theory of PredictionJournal of Applied Physics, 1950