High‐resolution multiple‐input–multiple‐output–inverse synthetic aperture radar imaging based on sparse representation. Issue 7 (1st August 2016)

• Record Type: Journal Article
• Authors: Yang, Jianchao; Su, Weimin; Gu, Hong
• Is Part Of: IET radar, sonar & navigation. Volume 10:Issue 7(2016)
• Page Start: 1277
• Page End: 1285
• Publication Date: 2016-08-01
• Subjects: MIMO radar -- synthetic aperture radar -- radar imaging -- image resolution -- image representation -- image reconstruction -- image filtering -- matched filters -- echo -- calibration -- Doppler radar -- radar resolution; sparse representation -- matched filtering -- envelope alignment -- MIMO‐ISAR cross‐range echo -- two‐dimensional sparse signal -- slow‐time domain -- spatial domain -- sparse reconstruction algorithm -- self‐calibration algorithm -- phase error correct -- target translational motion -- target spatial‐Doppler scene reconstruction -- spatial frequency -- Doppler frequency -- scatterer cross‐range coordinate -- high‐resolution MIMO‐ISAR imaging -- relative rotation angle reduction -- multiple input multiple output–inverse synthetic aperture radar; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2015.0517
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : In this study, a new method based on sparse representation is proposed for multiple‐input–multiple‐output (MIMO) radar imaging combining with inverse synthetic aperture radar (ISAR) technique. After matched filtering and envelope alignment, the MIMO–ISAR cross‐range echo is formulated as a two‐dimensional sparse signal with respect to the spatial and slow‐time domain. A joint self‐calibration and sparse reconstruction algorithm is developed to correct the phase error induced by the target's translational motion and reconstruct the spatial–Doppler scene of the target. Then, the linear relationship between the spatial and Doppler frequencies is utilised to solve the ambiguity of the spatial frequency. Finally, the unambiguous spatial frequency is translated into the cross‐range coordinate of the scatterer. Experimental results show that the proposed method is capable of precisely correcting the phase error and achieving high‐resolution MIMO–ISAR imaging. In addition, the relative rotation angle required for MIMO–ISAR imaging can also be reduced significantly.