Particle Swarm Optimization algorithm (PSO) is a popular stochastic searching optimization algorithm to solve complicated optimization problems. The approach of retrieving duct parameters from the sea-surface reflected radar clutter is also known as Refractivity From Clutter (RFC) technique. RFC technique provides the near-real-time duct parameters to evaluate the radio system performance, without adding any hardware. Basic principles of PSO and its applications and RFC technique are introduced. Evaporation duct is retrieved based on RFC technique using PSO. The performance of PSO is validated using experiment data launched at East China Sea, and compared with those of genetic algorithm (GA) and ant colony algorithm (ACA). The results indicate that PSO has the advantages of faster convergence and higher retrieval precision than the other two methods.
"Retrieving Evaporation Duct Heights from Radar Sea Clutter Using Particle Swarm Optimization (PSO) Algorithm," Progress In Electromagnetics Research M,
Vol. 9, 79-91, 2009. doi:10.2528/PIERM09090403
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