Open AccessThree‐dimensional SAR imaging of sea targets with low PRF sampling
Author(s) -
Wang Pengfei,
Liu Mei,
Wang Zhigui
Publication year - 2018
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2017.0363
Subject(s) - azimuth , synthetic aperture radar , computer science , artificial intelligence , sampling (signal processing) , inverse synthetic aperture radar , compressed sensing , computer vision , radar imaging , elevation (ballistics) , range (aeronautics) , tomographic reconstruction , iterative reconstruction , remote sensing , radar , geology , mathematics , engineering , optics , telecommunications , physics , geometry , filter (signal processing) , aerospace engineering
Three‐dimensional (3D) synthetic aperture radar (SAR) image formation provides the scene reflectivity estimation along azimuth, range, and elevation coordinates. A common 3D SAR focusing approach is compressed sensing (CS)‐based SAR tomography, but this technique brings image quality problems because of the undesired side‐lobes in the focused two‐dimensional (2D) images. Moreover, the amount of raw data, which is used for 3D imaging, is still very large. To reduce the amount of raw data and achieve satisfying 3D resolving ability, a novel 3D imaging method based on multidimensional CS (MCS) is proposed for multi‐baseline SAR. In this study, the multi‐baseline SAR 3D raw signals are presented in space‐time domain; and the proposed 3D imaging algorithm based on MCS is used to reduce the amount of raw data. The range, azimuth and elevation profiles can be reconstructed with an extremely low Pulse Recurrence Frequency (PRF) with this algorithm. Comparisons with the existing CS‐tomographic focusing method are also presented. Experimental results demonstrate that the proposed algorithm can efficiently solve the 3D imaging task with limited PRF sampling.