A Genetic Algorithm for Mid-Air Target Interception

paper presents a computational model that uses a modified Genetic Algorithm (GA) approach, to provide more accurate results for mid-air targets interception. The proportional navigation laws that have been practiced for many years for target interception have been deployed in this research. A revised GA is formulated to determine the optimal interception point by modifying the heuristic crossover. An interception point is computed in which the miss distance and missile flight times are minimized. The selections of proportional navigation constant (CN) and time-to-launch values are playing a key role in minimizing the interception error. The results suggest a minimized interception error with better accuracy for target interception.