Estimation of bias and scale factor trends in ESGM accelerometer

A filter with steady state gains is developed for on-line estimation of accelerometer bias and scale factor trends in the ESGM (Electrostatically Supported Gyro Monitor) navigation system. The method of approach is to initially derive a Kalman filter which optimally estimates the accelerometer trends. Both a ramp and random walk trend model are considered. Additionally, the effect of gravity anomaly is included in both models. The Kalman filter gains serve as the basis for the final choice of steady state gains.