Zero-Rate Offset Compensation for Dual-Mass Tuning Fork Micro-Machined Gyroscope Based on Back Propagation Neural Network

摘要

For the zero-rate offset of dual-mass tuning fork micro-machined gyroscope (DTMG), back propagation neural network (BPNN) is proposed to compensate the offset. The zero-rate offset data were tested as the training data and the verification data of BPNN. The experimental results prove that this method has strong nonlinear mapping capabilities. And it can effectively reduce the zero-rate offset of DTMG by more than one order of magnitude. Thus, DTMG can be applied to the field of inertial navigation with higher precision.