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The radar backscatter from the ocean surface, called sea clutter, is modulated due t o the surface wave field. The modulation introduces a spatio-temporal correlation of the sea clutter signal. A three-dimensional wavenumber frequency spectrum of the sea clutter is calculated from a time series of radar images with an FFT algorithm. Because of the non-linearity of the imaging process the image spectrum contains harmonics in addition t o the linear fundamental mode. These modes are localized at distinct surfaces in the wave number frequency space corresponding t o the scaled dispersion relation of surface gravity waves. Because of the localization of the spectral energy on dispersion shells, the aliasing effect due t o a temporal undersampling can be overcome. The dispersion shells are reconstructed over the Nyquist frequency barrier and for negative frequencies. The dispersion shells are used as spectral filters t o separate the modes from the clutter noise pedestal of radar image spectra. This pedestal shows the effect of the impulse response due t o the finite spatial resolution of the radar. The spectral energy of the wavenumber frequency spectrum is integrated over the frequency coordinate axis, with the positive solution of the dispersion relation of surface gravity waves as signal filter. With this spectral filter method an unambiguous wave number image spectrum is selected.An empirical calibration procedure is presented. This procedure is based on the correlation of the signal t o noise ratio with the significant wave height. The applicability of the method is shown using a radar and buoy data set. The spectral energies of fundamental mode, first harmonic, and the clutter component are compared. It was proved that the spectral energy of the clutter noise exceeds the spectral energy of the first harmonic mode by an order of magnitude, i.e. the physical background of the empirical calibration method is similar t o the method well established for wave spectra from single SAR images.The fundamental image spectrum is related t o the surface wave spectrum by an image transfer function.

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