Domain Decomposition Method for Propagation Prediction of Large-range Evaporation Duct

In order to solve the problems of long time, low efficiency, low precision, high performance of computer and failing to meet the needs of engineering in the study of the refractive index profile and propagation loss of large range atmospheric duct, a kind of non-overlapping domain decomposition method (DDM) combined with the least square support vector machine (LSSVM) is proposed. The training database is first produced by the forward propagation model, and the large area is decomposed into multiple sub-domains by non-overlapping DDM to make a large number of data effectively divided into small sample data in the sub-domain to train the least squares support vector machine and optimize the parameters of the least squares support vector machine. A fast prediction of propagation loss and refractive index profile of large range evaporation duct is achieved. The propagation loss of the parabolic equation and the true value of the refractive index profile are compared with the predicted data. The results show that the method improves the efficiency and accuracy of the refractive index profile and propagation loss of the large range evaporation duct, reduces the computer performance requirements, which is of universal significance for the prediction of the propagation loss and refractive index profile of large range atmospheric duct, and of great value to the elimination of the influence of duct on radar and communication equipment.