Prediction of Calibration Parameters of Platform Inertial Navigation System Based on Grey Combination Model

In order to solve the problem of insufficient utilization of historical test data of platform inertial navigation system (PINS), a calibration parameter prediction method based on grey combination prediction model is proposed. Firstly, the acquired values of PINS calibration parameters are preprocessed, and then an improved Grey Markov Combinatorial Prediction Model (IMGM) with double background value optimization is proposed, and finally the reliability of the model prediction is verified by the actual calibration parameters data. The results show that the forecasting parameter values can provide data support for the performance evaluation, performance prediction and fault prompting of the inertial navigation system.