On the Interpretation of Least Squares Collocation

摘要: One of the central issues in current geodetic data reduction is question how noise-corrupted measurements physical parameters, derived from two independent measurement processes, can be combined to obtain an optimal estimate parameters. The problem complicated further when there apriori information on a subset parameters estimated. combining surface gravitational anamolies with observations satellites determine earth’s geopotential coefficients important example this class problem. difficulties lead Moritzl propose least squares collocation algorithm as general approach reduction. Subsequent investigations have claimed validate Moritz’s conclusion that method more parameter estimation than classical squares, minimum variance or maximum likelihood methods2,3