Repeatability interval prediction for calibrated parameters of INS based on bootstrap method

In order to choose platform inertial navigation systems and evaluate their performances, the repeatability interval prediction should be made at current or future time points for each calibrated parameter of inertial navigation system. Considering that the calibrated parameter's repeatability of each inertial navigation system has different parameter distribution characteristics, and the repeatability of different batch of inertial navigation systems in the same storage life stage shares the same distribution characteristics, this paper proposes a weighted combination interval prediction method based on bootstrap method, and the average values of 1δ at the upper and lower bound of the prediction intervals are given as well. By applying the method in the repeatability interval prediction of accelerometer's calibrated bias in different batch of inertial navigation systems, the average accuracy of prediction interval 1δ is up to 71.88%, which shows that this method has good effects in short-range prediction, and has proper application value in repeatability performance evaluation of inertial navigation system according to the prediction range length.