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This paper analyses the convergence behavior of the least-squares state estimator. It is shown that the standard algorithm based on the Gauss-Newton method ignores second-order information. Under some conditions this information is essential for a good convergence. Examples show that an algorithm based on Newton's method reveals a more robust character.