Single snapshot DOA estimation using compressed sensing

This paper deals with the problem of estimating the Directions of Arrival (DOA) of multiple source signals from a single observation of an array data. In particular, an estimation algorithm based on the emerging theory of Compressed Sensing (CS) is analyzed and its statistical properties are investigated. We show that, unlike the classical Fourier beamformer, a CS-based beamformer (CSB) has some desirable properties typical of the adaptive algorithms (e.g. Capon and MUSIC). Particular attention will be devoted to the super-resolution property. Theoretical arguments and simulation analysis are provided in order to prove that the CSB can achieve a resolution below the classical Rayleigh limit.

[1]  Parikshit Shah,et al.  Compressed Sensing Off the Grid , 2012, IEEE Transactions on Information Theory.

[2]  Emmanuel J. Candès,et al.  Towards a Mathematical Theory of Super‐resolution , 2012, ArXiv.

[3]  Mats Viberg,et al.  On the resolution of The LASSO-based DOA estimation method , 2011, 2011 International ITG Workshop on Smart Antennas.

[4]  Bin Yang,et al.  Single snapshot DOA estimation , 2010 .

[5]  M. Kaveh,et al.  Sparse spectral fitting for Direction Of Arrival and power estimation , 2009, 2009 IEEE/SP 15th Workshop on Statistical Signal Processing.

[6]  Fulvio Gini,et al.  DOA estimation and multi-user interference in a two-radar system , 2009, Signal Process..

[7]  Fulvio Gini,et al.  Joint use of Σ and Δ channels for multiple radar target DOA estimation , 2005, 2005 13th European Signal Processing Conference.

[8]  F. Gini,et al.  Multibaseline cross-track SAR interferometry: a signal processing perspective , 2005, IEEE Aerospace and Electronic Systems Magazine.

[9]  Dmitry M. Malioutov,et al.  A sparse signal reconstruction perspective for source localization with sensor arrays , 2005, IEEE Transactions on Signal Processing.

[10]  E. Candès,et al.  Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.

[11]  A. Farina,et al.  Multiple radar targets estimation by exploiting induced amplitude modulation , 2003 .

[12]  F. Gini,et al.  Layover solution in multibaseline SAR interferometry , 2002 .

[13]  A. Farina,et al.  DOA estimation by exploiting the amplitude modulation induced by antenna scanning , 2002 .

[14]  Johann F. Böhme,et al.  A note on most favorable array geometries for DOA estimation and array interpolation , 1997, IEEE Signal Processing Letters.

[15]  K.M. Buckley,et al.  Single-snapshot DOA estimation and source number detection , 1997, IEEE Signal Processing Letters.

[16]  Keith Q. T. Zhang.  Probability of resolution of the MUSIC algorithm , 1995, IEEE Trans. Signal Process..

[17]  Petre Stoica,et al.  MUSIC, maximum likelihood, and Cramer-Rao bound , 1989, IEEE Transactions on Acoustics, Speech, and Signal Processing.

[18]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[19]  J. Capon.  High-resolution frequency-wavenumber spectrum analysis , 1969 .