An ALoGI PU Algorithm for Simulating Kelvin Wake on Sea Surface Based on Airborne Ku SAR

Area of Science:

• Remote Sensing
• Oceanography
• Signal Processing

Background:

• Airborne Synthetic Aperture Radar (SAR) provides high-precision, real-time observation of wave height variations.
• The Ku band is suitable for high-frequency airborne SAR applications.
• Phase Unwrapping (PU) is crucial for accurately retrieving wave height information from SAR interferograms.

Purpose of the Study:

• To derive a Phase Unwrapping (PU) expression using the Four Fast Fourier Transform (4-FFT) algorithm and a Gaussian operator.
• To propose and optimize an Adaptive LoG (ALoG) algorithm for improved PU performance.
• To evaluate the effectiveness of PU algorithms in simulating and analyzing sea-surface Kelvin wakes.

Main Methods:

• Derivation of a Laplacian of Gaussian (LoG) PU expression combined with 4-FFT and a Gaussian operator.
• Development of an Adaptive LoG (ALoG) algorithm utilizing adaptive variance and iterative optimization.
• Simulation of interferometric phase for wave height using Kelvin wake and height-to-phase models.
• Quantitative and qualitative evaluation of PU algorithms using Principal Component Analysis (PCA).

Main Results:

• The Adaptive LoG iteration (ALoGI) algorithm demonstrated superior Principal Component Analysis (PCA) scores across tested noise levels.
• Simulation experiments confirmed the ALoGI algorithm's effectiveness in high spatial resolution inversion of sea-ship surface height from Kelvin wakes.
• The ALoGI algorithm exhibited good stability and noise resistance.

Conclusions:

• The ALoGI algorithm represents a significant advancement in Phase Unwrapping for airborne SAR applications.
• The developed method is highly effective for analyzing complex sea-surface phenomena like Kelvin wakes.
• The algorithm's robustness makes it suitable for real-world applications with varying noise conditions.