Single-Snapshot Time-Domain Direction of Arrival Estimation under Bayesian Group-Sparse Hypothesis and Vector Sensor Antennas

─ In this work, an optimal single-snapshot, time domain, group-sparse optimal Bayesian DOA estimation method is proposed and tested on a vector sensors antenna system. Exploiting the group-sparse property of the DOA and the Bayesian formulation of the estimation problem, we provide a fast and accurate DOA estimation algorithm. The proposed estimation method can be used for different steering matrix formulations since the optimal standardization matrix is computed directly from the knowledge of the steering matrix and noise covariance matrix. Thanks to this, the algorithm does not requires any kind of calibration or human supervision to operate correctly. In the following, we propose the theoretical basis and details about the estimation algorithm and a possible implementation based on FISTA followed by the results of our computer simulations test. Index Terms ─ Bayesian optimization, DOA estimation, group-sparsity norm, single snapshot signal, vector sensor antennas.

[1]  Mauro Parise Exact EM field excited by a short horizontal wire antenna lying on a conducting soil , 2016 .

[2]  P. Rocca,et al.  Directions-of-Arrival Estimation Through Bayesian Compressive Sensing Strategies , 2013, IEEE Transactions on Antennas and Propagation.

[3]  Yaakov Tsaig,et al.  Extensions of compressed sensing , 2006, Signal Process..

[4]  Marc Teboulle,et al.  A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..

[5]  Mauro Parise,et al.  Transverse magnetic field of infinite line source placed on ground surface , 2015 .

[6]  Emmanuel J. Candès,et al.  Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? , 2004, IEEE Transactions on Information Theory.

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

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

[9]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[10]  Michael A. Saunders,et al.  Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..

[11]  Wei Zhu,et al.  Novel methods of DOA estimation based on compressed sensing , 2015, Multidimens. Syst. Signal Process..

[12]  Arye Nehorai,et al.  Vector-sensor array processing for electromagnetic source localization , 1994, IEEE Trans. Signal Process..

[13]  Paolo Rocca,et al.  Compressive Sensing in Electromagnetics - A Review , 2015, IEEE Antennas and Propagation Magazine.