Authors: Zhengwei Zhu Jianjiang Zhou
Publish Date: 2011/06/02
Volume: 18, Issue: 3, Pages: 809-
Abstract
A superresolution reconstruction approach of radar image using an adaptivethreshold singular value decomposition SVD technique was presented and its performance was analyzed compared and assessed detailedly First radar imaging model and superresolution reconstruction mechanism were outlined Then the adaptivethreshold SVD superresolution algorithm and its two key aspects namely the determination method of point spread function PSF matrix T and the selection scheme of singular value threshold were presented Finally the superresolution algorithm was demonstrated successfully using the measured syntheticaperture radar SAR images and a Monte Carlo assessment was carried out to evaluate the performance of the algorithm by using the input/output signaltonoise 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≥maxs 2/r inSNR were tested The experimental results indicate that when the singular value threshold is set as s max/r inSNR1/2 the superresolution algorithm provides a good compromise between too much noise and too much bias and has good reconstruction results
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