摘要
为了实现对船舶水下电场信号目标特征的控制,提出一种信号预测的方法。对测得的信号进行小波分解并分别在静电场和轴频电场频段进行重构。对高频的轴频电场信号构建自回归预测模型,对低频的静电场信号以灰色GM(1,1)模型进行拟合。将预测结果进行叠加得到对下一时刻电场信号的预测值。实测数据对该方法的检验结果表明:用该方法对船舶水下电场进行预测,电场的预测误差在原信号幅值的20%以内。
To weaken the strength of the signals, a prediction method was presented. The electric field signal was decomposed into a low frequency signal and several high frequency signals. The high frequency part was predicted with auto regressive prediction model and the low frequency part was predicted with GM （1,1） model. The prediction result was the superimposition of the respective prediction. Based on the measurement at sea, the simulation results show that the prediction error of the electric field can be controlled within 20% of the amplitude of the signal.
出处
《国防科技大学学报》
EI
CAS
CSCD
北大核心
2016年第6期168-172,共5页
Journal of National University of Defense Technology
基金
国家自然科学基金资助项目(51109215)
关键词
水下电场
预测模型
小波分解
灰色GM(1
1)模型
自回归模型
electric field in sea
prediction model
wavelet decomposition
gray G M （1 ,1 ） model
auto regressive model
