The Least Squares Method (LSM) is one of the most useful criteria for the adjustment of data where the number of observations is redundant and the system of equations, due to the presence of errors in experimental measurements, inconsistent. This method takes as a single solution that which minimizes the sum of the squared random errors, and is widely used in geodetic applications. The theoretical foundation involved in the LSM, containing the mathematical development of the method, is widespread in the geodetic community. However, in this paper, the goal is to present a theoretical review of the geometric interpretation of the LSM, and an alternative computation solution, derived from this interpretation. Two examples are also shown, where this geometric interpretation has been demonstrated numerically for problems involving two observations and a parameter, and also four observations and two parameters.
Adjustment of Observations; Least Squares Method; LSM Geometric Interpretation
