摘要
针对目前雨衰预测模型在Ka频段雨衰估计中复杂度高、计算量大的问题,提出了一种结构相对简单、计算量较小的自相关雨衰预测模型.该模型首先利用前导雨衰数据之间的自相关性,采用平均误差功率最小的原则计算出模型的参数,然后结合前导数据迭代推算出Ka频段各个频率点的雨衰值.仿真结果表明,不同的前导数据量和预测间隔具有不同的预测精度,在前导数据量为20、预测间隔为0.05 GHz时,新模型的雨衰量预测误差在整个Ka频段均达到10-5dB以下.
In order to reduce the complexity of current rain attenuation prediction models, a new auto-correlation rain attenuation prediction model is proposed. The model has the advantages of relatively simple structure and less computational consumption. The new model takes the advantage of the auto-correlation character of preamble dates, and computes the model parameters by minimizing the average error power. Then, the preamble data and model parameters are used to compute the rain attenuation at each frequency point in Ka band. Simulation results show that prediction precision varies with different prediction intervals and different amount of preamble data. The prediction error of the new model is less than 10^-5 dB in Ka band when the number of preamble data is 20 and the prediction interval is 0.05 GHz.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2011年第2期78-81,共4页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(60802053)
陕西省自然科学基金资助项目(2009JM8001-3)
关键词
KA频段
雨衰
预测模型
自相关
Ka band
rain attenuation
attenuation prediction model
auto-correlation
