Open AccessFast deconvolution method for angular super‐resolution imaging based on sub‐space embedding
Author(s) -
Wu Yang,
Zhang Yin,
Huang Yulin,
Yang Jianyu
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0154
Subject(s) - deconvolution , embedding , resolution (logic) , space (punctuation) , angular resolution (graph drawing) , computer science , superresolution , computer vision , physics , artificial intelligence , optics , algorithm , image (mathematics) , mathematics , combinatorics , operating system
This study presents a fast deconvolution method based on the sub‐space embedding for angular super‐resolution in radar forward‐looking imaging area. The ill‐posed character of convolution matrix causes the difficulty to improve angular resolution and the redundancy of matrix increases computational complexity. In this study, the sub‐space embedding theory is applied to reduce the redundancy of convolution matrix. Through the sketching matrix, the effective space of convolution matrix is extracted, which improves the computational efficiency and modifies ill‐posed character. Simulations and experimental results demonstrate that the proposed method offers a time complexity reduction without loss of performance.