Title :
Stability analysis of radome error and calibration using neural networks
Author_Institution :
Inst. of Autom. Control Eng., Feng Chia Univ., Taichung, Taiwan
fDate :
10/1/2001 12:00:00 AM
Abstract :
Theoretical and numerical simulation analyses for the radome refraction effect on stability and induced miss distance of missiles guided by proportional navigation are presented. Quantitative stability conditions are derived with respect to linear and nonlinear radome error. A novel neural network compensation scheme for radome error is also presented. It is shown that the proposed neural compensator can effectively reduce the influence resulting from radome error. Preliminary results indicate encouraging improvement in the miss distance and magnitude of the acceleration command
Keywords :
Monte Carlo methods; calibration; error compensation; feedforward neural nets; learning (artificial intelligence); military radar; missile guidance; radar antennas; radomes; Monte Carlo simulations; RF seekers; acceleration command; acquisition accuracy; calibration; closed-loop training; convolution integral; false line-of-sight rate; flight control; guided missiles; induced miss distance; missiles stability; multilayer feedforward neural network; neural network compensation scheme; open-loop training; proportional navigation; quantitative stability conditions; radar homing missiles; radome error; radome refraction effect; Adaptive control; Artificial neural networks; Calibration; Error compensation; Missiles; Multi-layer neural network; Navigation; Neural networks; Radar tracking; Stability analysis;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
