Abstract
In this paper, we consider retrieving individual wave components in a multi-directional sea wave model. To solve this problem, a currently and commonly used method is three-dimensional discrete Fourier transform (3D DFT) on the radar image sequence. However, the uniform frequency and the uniform wavenumber in a wavenumber frequency domain can not always strictly satisfy the dispersion relation, and the spectral leakage in both temporal and spatial domains exists due to the limited analysis area selected from an image sequence. As a result, the DFT method incurs undesirable error performance in retrieving directional wave components. By deeply investigating the data structure of the multi-directional sea wave model, we obtain a new and decomposable matrix representation for processing the wave components. Then, a novel successive cancellation method is proposed to efficiently and effectively extract individual wave components, whose frequency and wavenumber rigorously satisfy the liner dispersion relation. Thus, it avoids spectral leakage in the spatial domain. The algorithm is evaluated by using linear synthetic wave image sequences. The validity of the proposed novel algorithm is verified by comparing the retrieved parameters of amplitude, phase, and direction of the individual wave components with the simulated parameters as well as those obtained by using the 3D DFT method. In addition, the reconstructed sea field using the retrieved wave components is also compared with the simulated remote sensing images as well as those attained using the inverse 3D DFT method. All the simulation results demonstrate that our proposed algorithm is more effective and has better performance for retrieving individual wave components from the spatio-temporal remote sensing image sequences than the 3D DFT method.
Highlights
The ocean wave is one of the most common ocean undulation phenomena and is critically important for ocean research and ocean exploitation [1,2,3,4,5,6,7]
Neither the 1D time series of wave components, which is retrieved from the sea surface field, nor the individual wave components, which can be directly retrieved from the frequency wavenumber spectrum after a 3D discrete Fourier transform (DFT) on the radar image sequence, follow the requirement
Our primary goal in this paper is to propose a new successive cancellation algorithm, which is an alternative to the 3D DFT method and fully based on theory, to efficiently and effectively extract the individual wave components without any reference measurements, whose frequency and wavenumber rigorously satisfy the linear dispersion relation and which can be directly used to initialize the wave propagation model
Summary
The ocean wave is one of the most common ocean undulation phenomena and is critically important for ocean research and ocean exploitation [1,2,3,4,5,6,7]. Neither the 1D time series of wave components, which is retrieved from the sea surface field, nor the individual wave components, which can be directly retrieved from the frequency wavenumber spectrum after a 3D DFT on the radar image sequence, follow the requirement. In [15], based on a multi-directional sea wave model, a method using the 2D DFT on the acquired radar image to predict the sea surface field at a desired location and time was proposed. Our primary goal in this paper is to propose a new successive cancellation algorithm, which is an alternative to the 3D DFT method and fully based on theory, to efficiently and effectively extract the individual wave components without any reference measurements, whose frequency and wavenumber rigorously satisfy the linear dispersion relation and which can be directly used to initialize the wave propagation model.
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