Hwang Ji-Hwan, Kim Duk-Jin, Kang Ki-Mook
Research Institute of Basic Sciences, Seoul National University, Seoul 88026, Korea.
School of Earth and Environmental Science, Seoul National University, Seoul 88026, Korea.
Sensors (Basel). 2022 Apr 9;22(8):2890. doi: 10.3390/s22082890.
A multifunctional scatterometer system and optimized radar signal processing for simultaneous observation of various physical oceanographic parameters are described in this paper. Existing observation methods with microwave remote sensing techniques generally use several separate systems such as scatterometer, altimeter, and Doppler radar for sea surface monitoring, which are inefficient in system operation and cross-analysis of each observation data. To improve this point, we integrated separate measurement functions into a single observation system by adding a measurement function of Doppler frequency to the existing system. So it enables to simultaneously measure the range and polarimetric responses of backscattering as well as movements of the sea surface. Here, the simultaneous measurement function of Doppler frequency was implemented by sampling an FMCW (frequency modulated continuous wave) radar signal as 2D raw data consisting of fast- and slow-time samples, i.e., the range and backscattering of radar target signals are analyzed from the fast-time samples while the Doppler frequency by the radar target's movement extracts from the slow-time samples. Through the Fourier transformed-based range-Doppler signal process, distance (), backscattering (), and Doppler frequency () are sequentially extracted from the 2D raw data, and a correlation to the physical oceanographic parameters is analyzed. Operability of the proposed system was examed through total 3 times of field campaigns from June 2017 to August 2020 and the observation data retrieved by the radar measurement data (, , ) was also cross-analyzed with in-situ data: e.g., tide, significant wave height, and wind speed and direction. Differences in the comparative results as an observational accuracy are as follows. Tidal level (Root Mean Square Error 0.169 m ()), significant wave height (RMSE 0.127 m , 0.362 m (°)), wind speed (RMSE 1.880 m/s (), 2.094 m/s (°)) and direction (18.84° ()).
本文介绍了一种多功能散射仪系统以及用于同时观测各种物理海洋学参数的优化雷达信号处理方法。现有的微波遥感技术观测方法通常使用多个单独的系统，如散射仪、高度计和多普勒雷达来进行海面监测，这些系统在系统运行和各观测数据的交叉分析方面效率低下。为改善这一点，我们通过在现有系统中添加多普勒频率测量功能，将单独的测量功能集成到一个单一观测系统中。这样它就能够同时测量后向散射的距离和极化响应以及海面的运动。在这里，多普勒频率的同时测量功能是通过将调频连续波（FMCW）雷达信号采样为包含快时间和慢时间样本的二维原始数据来实现的，即从快时间样本中分析雷达目标信号的距离和后向散射，而从慢时间样本中提取雷达目标运动产生的多普勒频率。通过基于傅里叶变换的距离 - 多普勒信号处理，从二维原始数据中依次提取距离（）、后向散射（）和多普勒频率（），并分析其与物理海洋学参数的相关性。通过2017年6月至2020年8月总共3次野外试验对所提出系统的可操作性进行了检验，并且还将通过雷达测量数据（，，）获取的观测数据与现场数据进行了交叉分析：例如潮汐、有效波高以及风速和风向。作为观测精度的比较结果差异如下。潮汐水位（均方根误差0.169米（））、有效波高（均方根误差0.127米，0.362米（°））、风速（均方根误差1.880米/秒（），2.094米/秒（°））和风向（18.84°（））。
