High-resolution ISAR imaging of maneuvering targets based on the sparse representation of multiple column-sparse vectors

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• 作者：Xingyu He ; ^{hxy_19890708@163.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Ningning Tong ^{Tningning123@163.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Weike Feng ^{weikeF009@163.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Compressed sensing (CS) ; Inverse synthetic aperture radar (ISAR) ; Maneuvering target ; Multiple measurement vector ; Smoothed ℓ^{0ℓ0 norm (SL0)}
• 刊名：Digital Signal Processing
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：59
• 期：Complete
• 页码：100-105
• 全文大小：578 K

文摘

For inverse synthetic aperture radar (ISAR) imaging of a maneuvering target, the time-variance of Doppler shifts will produce blurred images over a long coherent processing interval (CPI). Compressed sensing (CS) theory indicates that the precise recovery of an unknown sparse signal can be achieved from a very limited number of measurements. A novel sparse reconstruction of multiple column-sparse vectors using an algorithm with a minor reconstruction error and low computational complexity is proposed here based on multiple measurement vectors (MMV) and the smoothed class="mathmlsrc">class="formulatext stixSupport mathImg" data-mathURL="/science?_ob=MathURL&_method=retrieve&_eid=1-s2.0-S105120041630121X&_mathId=si1.gif&_user=111111111&_pii=S105120041630121X&_rdoc=1&_issn=10512004&md5=1d323dd7d69affded281c9f11e4666ed" title="Click to view the MathML source">ℓ⁰class="mathContainer hidden">class="mathCode">${\ell }^0$ norm (SL0) algorithm. For ISAR imaging of maneuvering targets, the Doppler shifts remain nearly constant for a short CPI. The proposed algorithm can produce high resolution ISAR images of maneuvering targets with an extremely limited number of pulses. Simulation results demonstrate the effectiveness and computational efficiency of the proposed method.