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针对经典模型在Ka波段雨衰预测时存在涉及参数多、计算量大的问题,提出了基于差分平稳时序的预测方法.该方法利用前导雨衰值的差分变换建立预测模型,并通过对平稳时序的参数估计得到各频点的雨衰预测值,进而实现将传统的非线性预测转化为简便的线性预测.仿真结果表明:不同预测间隔、时序个数、差分次数下的预测精度不同,与Dissanayake-Allnut-Haidara模型相比在满足预测间隔0.1 GHz、时序数20、二次差分条件时预测误差可达10-3以下,同时表明极化方式对模型参数的影响可以忽略,验证了所提方法具备参数计算简单、预测精度高的优点.
Aiming at the problem that the classical model has many parameters and large amount of calculation in the prediction of rain and fall in Ka wave band, a prediction method based on differential stationary sequence is proposed, which uses the differential transformation of the preamble rain attenuation to establish the prediction model, The prediction of rain attenuation at each frequency is obtained, and then the traditional nonlinear prediction is transformed into a simple linear prediction.The simulation results show that the prediction accuracy under different prediction intervals, the number of time series and the difference orders are different from those of Dissanayake -Allnut-Haidara model, the prediction error can reach 10-3 or less when the prediction interval is 0.1 GHz, the time series number is 20 and the quadratic difference condition is satisfied, and the influence of the polarization mode on the model parameters is negligible, which verifies the proposed method With the parameter calculation is simple, the advantages of high accuracy.