Gyro drift prediction based on parallel recursive AP algorithm of volterra series

For forecasting the gyro drift tendency of a missle, a prediction model based on Volterra series is established by taking the time series of gyro's drift as study object, and a parallel recursive affine projection(AP) algorithm for nonlinear system based on Volterra series is presented in this paper. Taking the minimum norm of the Volterra kernel vector increments and certain constraints as the overall cost function, by the steepest descent principle, the adaptive updating formula of the Volterra kernel vector of each order is derived, and the matrix inverse lemma is applied to recursively estimate the inverse of autocorrelation matrix of Volterra subsystem of each order, thus the algorithm is derived. The algorithm is applied to prediction research on real gyro drift data of certain missle, and experiment results show that the algorithm has fast operation speed and high prediction precision.