Reconstruction of super-resolution spectra for the beamformed data in HF skywave radar

For economy, the digital beamforming(DBF) is used to transform a huge array outputs into the bearing ones at several expectable directions in HF skywave radar. However, as the target signal phases on the different array elements are mixed in the beamformed data, the resolvable super-resolution spatial spetra of the coherent targets within a beamwidth can not be directly constructed by the existing algorithms any more. Therefore, in this paper, an improved method for the reconstruction of these spatial spectra is investigated to solve the underlying problem. A so-called pseudo-inverse processing is used to transform the beamformed data to the equivalent array data on the peak of the detected target range-velocity spectra. Then, combined with the Toeplitz construction and the MUlitple Signal Classification (MUSIC) algorithm, the coherent targets are resolved and the azimuth estimates are improved. Since the window weighting is usually used in the beamforming, the different weighting effect on the pseudo-inverse processing is also discussed.