Theoretical review demonstrates the evolution of least-squares estimation in applied mathematics, highlighting the enduring influence of classical concepts on modern filtering algorithms.
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.''
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H.W. Sorenson (1970) studied this question.
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