Compensation of Temperature Drift of Micro Gyroscope by BP neural network algorithm

Micromachined gyroscope is easily affected by the working environment temperature and has temperature drift. In order to reduce the gyro output error caused by temperature change, the BP neural network is used to model and compensate the temperature drift error. After compensation, the zero output of the gyro is near 0°/s and does not change with temperature changes, the accuracy is greatly improved. The experimental results show that the compensation algorithm can effectively suppress the influence of temperature on the micro gyroscope sensor.