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access icon free Novel sparse apertures ISAR imaging algorithm via the TLS-ESPRIT technique

© The Institution of Engineering and Technology
Received 14/11/2019, Accepted 18/02/2020, Revised 04/02/2020, Published 21/02/2020

The prevalent imaging method in inverse synthetic aperture radar (ISAR) system is range-Doppler (RD) method, which is implemented by the fast Fourier transformation (FFT). FFT is computationally efficient, but it comes with a price – the problems of wide main-lobes and high side-lobes, especially under the sparse apertures condition. In addition, the resolution of RD method is determined by the radar parameters, which poses limitation to super-resolution imaging, multi-tasking and cognitive reconfigurable applications. In this study, the authors propose a novel super-resolution ISAR imaging method based on the total least squares-estimation of signal parameters via rotational invariance technique (TLS-ESPRIT). The locations and intensities of the scatterers are obtained by employing the ESPRIT algorithm and the least squares technique. Then the ISAR image is formulated, having circumvented all of the above-mentioned limitations. Experiments based on simulated and real measured data validate the effectiveness of the proposed method.

Inspec keywords: radar imaging; image resolution; fast Fourier transforms; least squares approximations; synthetic aperture radar

Other keywords: rotational invariance technique; wide main-lobes; high side-lobes; ISAR image; RD method; radar parameters; TLS-ESPRIT technique; signal parameters; novel sparse apertures ISAR imaging algorithm; FFT; sparse apertures condition; prevalent imaging method; super-resolution imaging; novel super-resolution ISAR; inverse synthetic aperture radar system; cognitive reconfigurable applications; ESPRIT algorithm; range-Doppler method; least-squares technique; fast Fourier transformation

Subjects: Interpolation and function approximation (numerical analysis); Radar equipment, systems and applications; Integral transforms; Optical, image and video signal processing

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