Gyro drift prediction based on reduced parameter second-order Volterra series
基于少参数二阶Volterra级数的陀螺漂移预测

For forecasting the nonlinear time series of gyro's drift angle rate, this paper presented an affine projection AP adaptive identification algorithm based on reduced parameter second-order RPSO Volterra series, established a prediction model based on RPSO Volterra series. It deduced two similar iterative formulas for the prediction model's two parameter vectors, because that their position could be interchanged. It presented the whole steps of the proposed algorithm. It used the real gyro drift data to validate the proposed algorithm, gained the accurate prediction immediately.