Compressed sensing in array signal processing based on modulated wideband converter

Nyquist theory is a serious obstacle to the wideband signal processing, which has been broken by compressed sensing theory. Modulated wideband converter can sample wideband signals with subNyquist frequency. In array signal processing, to bring down the sampling rate for the wideband signal is especially an essential issue. This paper proposes a new architecture based on modulated wideband converter, which can be used in array wideband signal processing. It makes full use of the parallelism of the modulated wideband converter and the sparsity of the special wideband signal, and the existing algorithms for L-shaped array can be used in the proposed architecture directly. The theoretical analysis and simulations prove its capableness of compressed sensing in array signal processing.

[1]  S. Kirolos,et al.  Analog-to-Information Conversion via Random Demodulation , 2006, 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software.

[2]  Richard G. Baraniuk,et al.  Theory and Implementation of an Analog-to-Information Converter using Random Demodulation , 2007, 2007 IEEE International Symposium on Circuits and Systems.

[3]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[4]  Yonina C. Eldar,et al.  Sub-Nyquist processing with the modulated wideband converter , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[5]  Wei Ping.  An Automatic Pairing Method for 2-D Direction of Arrival Estimation , 2013 .

[6]  Yonina C. Eldar,et al.  From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals , 2009, IEEE Journal of Selected Topics in Signal Processing.

[7]  Yonina C. Eldar,et al.  Efficient sampling of sparse wideband analog signals , 2008, 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel.

[8]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.