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- W2968576413 abstract "This study proposes a joint sparse algorithm based on Bayesian compressive sensing to improve full polarisation inverse synthetic aperture radar (ISAR) imaging performance. The proposed method not only uses the sparseness of each single channel polarisation, but also takes into account the correlation of amplitude information between single-polarised channels. Through the comprehensive use of single channel polarisation imaging results, a better full-polarisation imaging result is achieved. Simulation results are used to verify the effectiveness of the method." @default.
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- W2968576413 date "2019-08-15" @default.
- W2968576413 modified "2023-10-18" @default.
- W2968576413 title "Full polarisation ISAR imaging based on joint sparse Bayesian compressive sensing" @default.
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- W2968576413 doi "https://doi.org/10.1049/joe.2019.0365" @default.
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