Performance comparison of GA,PSO, and DE approaches in estimating low atmospheric refractivity profiles |
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Authors: | Bo Wang Zhensen Wu Zhenwei Zhao |
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Institution: | 1.School of Science,Xidian University,Xi’an,Shaanxi, China;2.China Research Institute of Radiowave Propagation,Qingdao,Shandong, China |
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Abstract: | Particles swarm optimization (PSO) and differential evolution (DE) algorithms based on optimization are employed to estimate
low atmospheric refractivity profiles from radar sea clutter. Low atmospheric refractivity profiles are modeled as evaporation
ducts. The objective functions, which are used to evaluate the fit of simulated and measured power in estimation procedures,
are also investigated at different frequencies such as L-, S-, C- and X-frequency at 10 m/s wind speeds. The results show
that all the objective functions are multi-peak functions. The Adjusted Barton Model of radar cross section (RCS) is adopted.
PSO and DE algorithms are compared with genetic algorithm (GA) by 200 Monte Carlo simulation estimations. Simulation results
indicate that DE has the best global search ability, and PSO has the highest success probability. According to the statistical
results, PSO algorithm with the population size 30 is the appropriate way for evaporation duct estimation. |
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Keywords: | |
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