Application of PSO-GACGA in Sea-Clutter Doppler Spectrum Modeling

摘要

In the field of sea clutter research, the key of sea targets recognition and detection is that accuracy estimated parameters of the Doppler Spectrum modeling through the optimal solution search algorithm. Our work provides two ways to improve heuristic search algorithm. One is CGA(Continuesmutation Genetic Algorithm) that cloud prevent Hamming Cliff, which is considered as GA’s inherent issue. The other is that the PSO-GA (Particle Swarm Optimization and Genetic Algorithm) and PSO-CGA (Particle Swarm Optimization and Continuesmutation Genetic Algorithm) obtained by combining algorithms, which can take advantages of the original methods and increase the individuals utilization rate. Both these method can reduce the error of the obtained results without increase solving time. In addition, we also proposes a new evaluation method of the heuristic search algorithm to efficiency measure algorithms.