Zhai Limin, Gong Yifan, Zhang Xiangkun
Key Lab of Microwave Remote Sensing, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China.
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100048, China.
Sensors (Basel). 2025 Jul 21;25(14):4508. doi: 10.3390/s25144508.
The airborne Synthetic Aperture Radar (SAR) has the advantages of high-precision real-time observation of wave height variations and portability in the high frequency band, such as the Ku band. In view of the Four Fast Fourier Transform (4-FFT) algorithm, combined with a Gaussian operator, a Laplacian of Gaussian (LoG) Phase Unwrapping (PU) expression was derived. Then, an Adaptive LoG (ALoG) algorithm was proposed based on adaptive variance, further optimizing the algorithm through iteration. Building the models of Kelvin wake on the sea surface and height to phase, the interferometric phase of wave height can be simulated. These PU algorithms were qualitatively and quantitatively evaluated. The Principal Component Analysis (PCA) scores of the ALoG iteration (ALoGI) algorithm are the best under the tested noise levels of the simulation. Through a simulation experiment, it has been proven that the superiority of the ALoGI algorithm in high spatial resolution inversion for the sea-ship surface height of the Kelvin wake, with good stability and noise resistance.
机载合成孔径雷达(SAR)具有在高频波段(如Ku波段)高精度实时观测波高变化和便携性的优点。针对四阶快速傅里叶变换(4-FFT)算法,结合高斯算子,推导了高斯-拉普拉斯(LoG)相位解缠(PU)表达式。然后,基于自适应方差提出了一种自适应LoG(ALoG)算法,并通过迭代进一步优化该算法。建立海面开尔文尾流和高度到相位的模型,可以模拟波高的干涉相位。对这些PU算法进行了定性和定量评估。在模拟的测试噪声水平下,自适应LoG迭代(ALoGI)算法的主成分分析(PCA)得分最佳。通过模拟实验,证明了ALoGI算法在开尔文尾流海面船舶表面高度的高空间分辨率反演中具有优越性,具有良好的稳定性和抗噪声能力。