Super-resolution reconstruction of synthetic-aperture radar image using adaptive-threshold singular value decomposition technique

作者：Zhu Zheng wei^*; Zhou Jian jiang

来源：Journal of Central South University of Technology, 2011, 18(3): 809-815.

DOI：10.1007/s11771-011-0766-7

• synthetic-aperture radar
• image reconstruction
• super-resolution
• singular value decomposition
• adaptive-threshold

A super-resolution reconstruction approach of radar image using an adaptive-threshold singular value decomposition (SVD) technique was presented, and its performance was analyzed, compared and assessed detailedly. First, radar imaging model and super-resolution reconstruction mechanism were outlined. Then, the adaptive-threshold SVD super-resolution algorithm, and its two key aspects, namely the determination method of point spread PSF) matrix T and the selection scheme of singular value threshold, were presented. Finally, the super-resolution algorithm was demonstrated successfully using the measured synthetic-aperture radar (SAR) images, and a Monte Carlo assessment was carried out to evaluate the performance of the algorithm by using the input/output signal-to-noise ratio (SNR). Five versions of SVD algorithms, namely 1) using all singular values, 2) using the top 80% singular values, 3) using the top 50% singular values, 4) using the top 20% singular values and 5) using singular values s such that s(2)>= max(s(2))/r(inSNR) were tested. The experimental results indicate that when the singular value threshold is set as s(max)/(r(inSNR))(1/2), the super-resolution algorithm provides a good compromise between too much noise and too much bias and has good reconstruction results.

• 出版日期2011-6
• 单位西南科技大学; 南京航空航天大学