Offshore Surface Evaporation Duct Joint Inversion Algorithm Using Measured Dual-Frequency Sea Clutter

Abstract

In this article, high-precision joint inversion of evaporative duct based on the dual-frequency radar sea clutter data is analyzed to study the abnormal duct environmental phenomenon that occurs over offshore surfaces. As the information of duct environment retrieved by radars with different frequencies is inconsistent, a joint optimization model with dynamic penalty factor is proposed, which can improve the degree of conformity between the measured clutter power and the modeled clutter power. Then, a parallel crossover quantum particle swarm optimization algorithm is used to jointly invert the objective function, which adaptively processes the inputs involved in the crossover and effectively improves the convergence of the inversion. Compared with the single-frequency model commonly used in engineering, the average relative error of the duct height of the dual-frequency joint optimization model is reduced by 3.13%, and the average relative error of the duct intensity is reduced by 6.34%, verifying the effectiveness of this method.

Keywords

• Dynamic penalty factor
• evaporation duct
• joint inversion
• objective function
• radar sea clutter