This　paper　investigates　generalized　pilot　estimators　of　covariance　matrix　in　the　presence　of　missing　data.　When　the　random　samples　have　only　bounded　fourth　moment,　two　kinds　of　generalized　pilot　estimators　are　provided,　the　generalized　Huber　estimator　and　the　generalized　truncated　mean　estimator.　In　addition,　we　construct　thresholding　generalized　pilot　estimator　for　a　kind　of　sparse　covariance　matrices　and　establish　the　convergence　rates　in　terms　of　probability　under　spectral　and　Frobenius　norms　respectively.　Moreover,　the　convergence　rates　in　sense　of　expectation　are　also　given　under　an　extra　condition.　Finally,　simulation　studies　are　conducted　to　demonstrate　the　superiority　of　our　method.