A robust direct approach for calculating measurement error covariance matrix

Calculation of the measurement error covariance matrix is an essential requirement in data reconciliation methods. It is common practice to assume that the measurement errors are normal and have a known covariance matrix. A new robust method of measurement error covariance matrix calculation is presented. This approach directly treats the measured process variables but uses an M-estimator to reject the outlier and tunes the measured values for deviations from steady-state