ITERATIVE LEARNING IDENTIFICATION OF AERODYNAMIC DRAG CURVE FROM TRACKING RADAR MEASUREMENTS

The aerodynamic drag coefficient curve of spin-stabilized projectiles is very important to the fast generation of accurate firing tables. To identify it from Doppler tracking radar measured velocity data in fli ght tests, an iterative learning concept (ILC) is applied. High-order ILC algorithms are proposed. Convergence conditions are given in a gen eral problem setting. A 3-DOF point mass trajectory prediction model i s proposed. The learning gains, which vary with respect to both time a nd iteration number, have been used for a faster convergence compared to the constant learning parameter choices. Furthermore, in this paper , a bi-linear ILC scheme is proposed to produce even faster learning c onvergence. The flight testing data reduction results of an actual fir ing practice demonstrate that the iterative learning method is very ef fective in curve identification. Copyright (C) 1997 Elsevier Science L td.