Implementation of Cultural Genetic Algorithm for Radar Network Coverage

The cultural genetic algorithm-based method for radar network coverage presented in this study can be effectively applied to optimization scenarios involving multiple targets. This approach primarily simulates the evolutionary process of cultural genetic algorithms to identify optimal radar network configurations that achieve comprehensive coverage of target areas. The algorithm integrates the advantages of individual learning and population learning, demonstrating strong performance in multi-objective optimization problems. Key implementation aspects include designing chromosome encoding schemes to represent radar positions and parameters, establishing belief space structures to store cultural knowledge, and developing inheritance operators that combine genetic evolution with cultural transmission. Code implementation typically involves fitness functions evaluating coverage rates, crossover/mutation operations for solution space exploration, and influence functions that apply cultural knowledge to guide the evolutionary process. By adopting this cultural genetic algorithm-based radar networking technology, significant improvements can be achieved in radar network coverage capabilities, resulting in enhanced target monitoring and detection effectiveness across complex multi-target environments.