Abstract
In recent years, the compressed sensing theory has been widely used in sparse aperture radar imaging. The inverse synthetic aperture radar (ISAR) imaging based on the sparse aperture echo of V-style frequency modulation (V-FM) waveform, which can mitigate the ambiguity appeared in range and velocity, has been proposed in this paper. After analyzing and interpreting the reason why the VFM signal pulse compression needs to use dual channels, we built the VFM waveform sparse echo model and analyze the causes of echo sparseness. A modified weighted compressive sensing (MWCS) algorithm is proposed to obtain high-resolution images under strong noise environment. The innovation of this paper lies in the new weighting method and the iterative reconstruction algorithm. The experimental results are shown to demonstrate the validity of the proposed method.
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