【摘要】 海杂波是雷达在海洋表面采集到的海面电磁散射回波.受海洋环境要素(风速、风向、浪高、浪向等)和雷达参数的影响,其幅度随时间具有随机起伏性,海杂波的幅度预测精度的提高有助于增加目标检测准确度.本文结合海杂波非高斯非线性的特点,提出了基于门控循环神经网络的海杂波幅度预测方法.通过对IPIX雷达和P波段雷达海杂波实测数据的预测分析,结果表明,本文方法相对已有传统方法具有更高的预测精度.更多还原

【Abstract】 Sea clutter is the sea surface electromagnetic scattering echo collected by the radar on the ocean surface. Affected by marine environmental factors(wind speed, wind direction, wave height, wave direction, etc.) and radar parameters, its amplitude has fluctuations with time and the accuracy of sea clutter amplitude prediction helps to increase target detection accuracy. Combined with the non-Gaussian and nonlinearity characteristics of sea clutter, the sea clutter amplitude prediction method based on gated feedback recurrent neural network is proposed. Through the prediction analysis of the sea clutter data, the results show that the proposed method has higher prediction accuracy than the traditional prediction methods.更多还原