Optimization of Radar Cross Section and Drag coefficient of Ogive Nose Using the NSGA-II Algorithm

Designers try to reduce missiles’ drag coefficients, but many of the geometrical changes that reduce the drag coefficient can increase the radar cross section of the missile. So, authors decided to solve this problem by missile optimization. In this study, missile Ogive nose is optimized using multi-objective genetic algorithm while the length of missile is kept constant. Objective functions are drag coefficient and radar cross section (RCS). Ogive nose was tested in mach number of 2.01 and radar systems were designed to operate at high frequencies between 4-6 GHz. The drag coefficient was calculated by CFD code and was compared with experimental results. Then, radar cross section was calculated with the commercial HFSS program. Finally, objective functions were optimized using non-dominate sorting genetic algorithm (NSGA-II) and the objectives were both minimized to establish the Pareto front. Pareto front shows the best possible design points for the objective functions. Compared with the initial model, the optimum model achieves a decrease of 47% and 14% in the drag coefficient and the radar cross section respectively.