In this paper, we present a study on using weightedtotal least squares method for parameter estimation of errorsin-variables models with quadratic regressors. The statistics oferror is analyzed to fill in the gap between basic assumptions inweighted total least squares and our case. A modified Cram´er-Rao lower bound is introduced for error quantification in theproposed method. We perform evaluations based on simulationswith comparisons to standard least squares and generalized totalleast squares. Numerical results show that the proposed methodoutperforms the others in terms of estimation accuracy