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    We developed a new super-resolution algorithm to improve terahertz (THz) near-field synthetic aperture radar (NSAR) imaging. This method significantly enhances image resolution, overcoming limitations of previous approaches for THz technology applications.

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    Area of Science:

    • Electromagnetics
    • Imaging Science
    • Optics

    Background:

    • Terahertz (THz) near-field synthetic aperture radar (NSAR) imaging suffers from low resolution.
    • Limitations include narrow antenna beamwidth and unaddressed electromagnetic wave loss in prior algorithms.
    • Enhanced resolution is crucial for advancing THz technology applications.

    Purpose of the Study:

    • To propose and evaluate a super-resolution algorithm for THz NSAR imaging.
    • To significantly improve the lateral resolution of reconstructed THz images.
    • To address the limitations of existing NSAR imaging algorithms.

    Main Methods:

    • Utilized the forward mathematical model of the NSAR imaging system.
    • Employed the back-projection algorithm (BPA) to compute the point spread function (PSF).
    • Applied deconvolution to BPA-reconstructed NSAR images for resolution enhancement.

    Main Results:

    • The proposed algorithm successfully enhanced the lateral resolution of THz NSAR images.
    • Experimental results demonstrated a resolution of 0.67λ, a substantial improvement.
    • Simulations and experiments validated the effectiveness of the developed method.

    Conclusions:

    • The novel super-resolution THz NSAR imaging algorithm offers significant resolution improvements.
    • This advancement has the potential to broaden the applications of THz imaging.
    • The method overcomes key limitations in current THz NSAR imaging techniques.