Fast deconvolution method for angular super-resolution imaging based on sub-space embedding

The Journal of Engineering

Yang Wu¹  Yulin Huang¹  Jianyu Yang¹  Yin Zhang¹ 

[1] University of Electronic Science and Technology of China;

关键词: image resolution;    deconvolution;    computational complexity;    radar imaging;    matrix algebra;    convolution;    fast deconvolution method;    convolution matrix;    redundancy;    sub-space embedding theory;    angular super-resolution imaging;    computational complexity;    radar forward-looking imaging;    ill-posed character;   

DOI  :  10.1049/joe.2019.0154

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown