Single-Snapshot Time-Domain Direction of Arrival Estimation under Bayesian Group-Sparse Hypothesis and Vector Sensor Antennas
Keywords:
Bayesian optimization, DOA estimation, group-sparsity norm, single snapshot signal, vector sensor antennasAbstract
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.
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R. Roy and T. Kailath, “ESPRIT-estimation of signal parameters via rotational invariance techniques,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37, no. 7, pp. 984-995, 1989.
R. Schmidt, “Multiple emitter location and signal parameter estimation,” IEEE Transactions on Antennas and Propagation, vol. 34, no. 3, pp. 276- 280, 1986.
D. L. Donoho, “Compressed sensing,” IEEE Transactions on Information Theory, vol. 52, no. 4, 1289-1306, 2006.
D. L. Donoho and Y. Tsaig, “Extensions of compressed sensing,” Signal Processing, vol. 86, no. 3, pp. 533-548, 2006.
S. S.Chen, D. L. Donoho, and M. A. Saunders, “Atomic decomposition by basis pursuit,” SIAM Review, vol. 43, no. 1, pp. 129-159, 2001.
E. J. Candes and T. Tao, “Near-optimal signal recovery from random projections: Universal encoding strategies,” IEEE Transactions on Information Theory, vol. 52, no. 12, pp. 5406-5425, 2006.
W. Zhu and B. X. Chen, “Novel methods of DOA estimation based on compressed sensing,” Multidimensional Systems and Signal Processing, vol. 26, no. 1, pp. 113-123, 2015.
M. Carlin, P. Rocca, G. Oliveri, F. Viani, and A. Massa, “Directions-of-arrival estimation through Bayesian compressive sensing strategies,” IEEE Transactions on Antennas and Propagation, vol. 61, no. 7, pp. 3828-3838, 2013.
A. Massa, P. Rocca, and G. Oliveri, “Compressive sensing in electromagnetics - A review,” IEEE Antennas and Propagation Magazine, vol. 57, no. 1, pp. 224-238, 2015.
A. Nehorai and E. Paldi, “Vector-sensor array processing for electromagnetic source localization,” IEEE Transactions on Signal Processing, vol. 42, no. 2, pp. 376-398, 1994.
A. Beck and M. Teboulle, “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,” SIAM Journal on Imaging Sciences, vol. 2, no. 1, pp. 183-202, 2009.
M. Parise, “Exact EM field excited by a short horizontal wire antenna lying on a conducting soil,” AEU - International Journal of Electronics and Communications, vol. 70, pp. 676-680, 2016.
M. Parise, “Transverse magnetic field of infinite line source placed on ground surface,” Electronics Letters, vol. 51, pp. 1478-1480, 2015.
M. Parise, “An exact series representation for the EM field from a circular loop antenna on a lossy half-space,” IEEE Antennas and Wireless Propagation Letters, vol. 13, pp. 23-26, 2014.