NUFFT-based fast reconstruction for sparse microwave imaging

Abstract

Compressive sensing (CS) theory has been applied to sparse microwave imaging in many ways that provide better performance and significantly reduce the sampling rate. However, the computational complexity of reconstruction puts strict constraint on some practical applications with large-scale problems in radar imaging. In this paper, we propose a novel fast reconstruction scheme by realizing the traditional matched filtering with CS technique, which maintains the good performance of matched filtering with a reduced number of observations. Meanwhile, a new sparse basis is formed which offers excellent potential for reducing the computational complexity in reconstruction with fast Fourier transform (FFT) and nonuniform FFT, i.e. NUFFT, where the computational complexity can decrease from to . The feasibility and efficiency of the proposed scheme are validated as well through both numerical simulations and raw data processing results.

Acknowledgments

This work was supported by the National Basic Research Program of China (2010CB731903) and in part by the National Natural Science Foundation of China (60901056, 61072112). The authors would also like to thank the anonymous reviewers for improving the quality of this paper.