Modified 'Current' Statistical Model Filtering Algorithm for Carrier Acceleration Calculation

摘要

Carrier acceleration is an important factor that influences the solution of the gravity anomaly in airborne gravimetry. The development of the airborne gravimetry has put forward a higher requirement to carrier acceleration. Considering the complex case of high-flying carrier in airborne gravimetry, in order to improve the solution accuracy of carrier acceleration, this paper adopt the Kalman filter method based on "Current" Statistical Model to solve the problem. For the characteristics of carrier acceleration. The fuzzy membership function and the Interacting Multiple Model algorithm are used to adjust the acceleration limits and motor frequencies of the "Current" Statistical Model. An improved "Current" Statistical Model algorithm is proposed to solve the carrier acceleration of airborne gravimetry, and then the filtering results are smoothed by the RTS smoothing. Finally, the proposed algorithm is validated by simulation experiments, the simulation results show that the proposed method is superior than the existing method position differential method in solving carrier acceleration, and the solution accuracy is improved greatly.