基于神经网络分类的星载雷达高度计近岸回波处理方法

Coastal Waveforms Processing Method for Spaceborne Radar Altimeter based on Neural Network Classification

对HY-2B卫星雷达高度计香港近岸波形进行了统计分析,将近岸非海洋波形分为似海洋波形、似陆地波形、单锥波形。在此基础上,提出基于神经网络分类的星载雷达高度计近岸回波处理方法,提取7项波形特征作为回波分类的输入,构建误差逆传播神经网络(Back propagation,BP),不同的波形类别对应不同的重跟踪方法。其中针对似海洋波形,提出异常波峰剔除的重跟踪方法,有效提高了似海洋波形的重跟踪成功率。使用Jason-2卫星雷达高度计近岸数据进行实验,结果表明重跟踪成功率和数据有效性均得到提高;利用HY-2B卫星雷达高度计直湾岛海域数据进行实验,并将验潮站数据作为参照标准,重跟踪得到的海面高与验潮站的海面高进行差值比较,该方法得到差分序列的标准差为6.5 cm,优于传统处理方法的14.5 cm。

A statistical analysis of the HY-2B satellite radar altimeter near-shore waveform in Hong Kong is car⁃ried out.The coastal non-ocean waveforms were divided into three categories:ocean-like waveform,land-like waveform and single cone waveform.On this basis,this paper proposes a coastal waveform processing approach based on neural network classification.Seven waveform features were extracted as the inputs for classification,and then a BP(Back propagation)neural network classifier was constructed.Different types of waveforms are handled differently.For ocean-like waveforms,an innovative method of removing abnormal samples before re⁃tracking was proposed,which effectively improved the waveform retracking success rate.Experiments with Ja⁃son-2 satellite radar altimeter near-shore data show that the success rate of retracking and the validity of the da⁃ta have been improved.Experiments are performed using the sea area data of Zhiwan Island from the HY-2B satellite radar altimeter,and the tide gauge station data is used as a reference standard.The sea level height ob⁃tained by retracking is compared with the sea level height of the tide gauge station.The standard deviation of the difference sequence obtained by the method in this paper is 6.5 cm,which is better than the 14.5 cm of the tradi⁃tional processing method.