Stochastic Model

A stochastic model describes the statistical properties of measurement errors and parameter uncertainties within a geodetic estimation process. It defines how observations are weighted, including assumptions about variances, covariances, correlations, and temporal noise characteristics (e.g., white noise, colored noise).

In geodesy, the stochastic model is a crucial component of least squares adjustment and Kalman filtering. It directly influences the estimated station coordinates, velocities, tropospheric parameters, gravity field coefficients, and Earth orientation parameters. An appropriate stochastic model ensures realistic uncertainty estimates, reliable variance–covariance information, and consistent combination of multi-technique geodetic solutions.