Variance-covariance Component Estimation Method Based on Generalization Adjustment Factor

The existing variance-covariance component estimation(VCE) theory and its defects are analyzed and briefly described.A generalization adjustment factor was developed from the adjustment factor concept,and both generalization closure error and its covariance matrix are investigated based on the generalization adjustment model.A novel VCE method including four basic function models is presented using the generalization adjustment factor.The relationship between four function models and VCE analytical or iterative solution properties is effectively revealed by the generalization adjustment factor.Triangulateration network adjustment results show that the VCE iteration solution lost fewer optimal statistical properties found in the LS criterion.The VCE analytical solution,only for the condition function model provides the optimal statistical properties meeting the LS criterion.