Considering rocket double-redundant strapdown control system consisting of six twodimension-of-freedoms gyros

advantages of integrated hardware redundancy and analytical redundancy

an advanced method for gyro fault diagnosis is designed; by using neural network observer

not only the problem which the fault diagnosis method based on hardware redundancy could not solve is able to be solved

but also the weakness of traditional analytical redundancy method could be overcome; by gyros’ adaptive thresholds

the robustness of fault diagnosis is improved; and it achieves the recovery of a fault gyros’ data.