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DoA estimation by means of Bayesian Compressive Sensing

 
 
The efficient exploitation of the available mobile communication channels is a very important issue, which is motivated by the ever-growing number of users that can interact at the same time with a base station. For this reason, it is necessary to develop methods which are able to improve the performances of transmitting/receiving systems in mobile communication networks. Toward this end, the use of antenna array can provide higher system capacities by providing narrow beam toward the user of interest, while nulling other users not of interest. Another advantage of Antenna Arrays is that the multipath fading (i.e. the reception of multiple copies of the same signal due to multiple reflections) can be eliminated by nulling multipath signals. In order to implement such kinds of strategies, the first step is the estimation of the direction of arrival (DoA) of the desired and undesired signals impinging on the antenna array. The information gathered in this step are fundamental to drive the successive beamforming process.
   
Smart Antennas, Radio Astronomy, Search and Rescue Services, Location Systems, Homing systems, Warning systems


 

Smart Atennas
Target Tracking Radar System
 

The reasearch activities of the Members of the ELEDIA Research Center are aimed at the development of innovative methdologies for the solution of the DoA estimation problem. In particular the under-development strategies are based on the exploitation of Bayesian Compressive Sensing (BCS) for the estimation of the received spatial signal spectrum. The main advantages of this method are:

  1. It enables the achievement of accurate estimations even with a limited number of snapshots, making this techniques suitable for real-time applications.
  2. The performances of the method are not affected by the correlation among the impinging signals, making this method approprate for multipath scenarios.
  3. Statistical assumptions on the impinging signal are not necessary.
  4. The knowledge of the number of signals is not needed.

 
Large Number Of Signals

 
Closely Spaced Sources

Keywords: Direction-of-Arrival estimation, Bayesian Compressive Sampling (BCS), Smart Antennas.


See Also
  • G. Oliveri, P. Rocca, and A. Massa, "A Bayesian-Compressive-Sampling-Based Inversion for Imaging Sparse Scatterers," IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 10, pp. 3993-4006, Oct. 2011
    doi:10.1109/TGRS.2011.2128329
  • 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, Jul. 2013.doi:10.1109/TAP.2013.2256093
  • M. Carlin, P. Rocca, G. Oliveri, and A. Massa, "Bayesian Compressive Sensing as applied to Direction-of-Arrival estimation in planar arrays," Journal of Electrical and Computer Engineering, vol. 2013, pp. 1-13, 2013.
    doi:10.1155/2013/245867
  • M. Carlin, P. Rocca, "A Bayesian compressive sensing strategy for direction-of-arrival estimation," 6th European Conference on Antennas and Propagation (EuCAP 2012), Prague, Czech Republic, pp. 1508-1509, 26-30 Mar. 2012.
    doi:10.1109/EuCAP.2012.6206667
  • M. Carlin, P. Rocca, G. Oliveri, and A. Massa, "Multi-task Bayesian compressive sensing for direction-of-arrival estimation," IEEE International Conference on Wireless Information Technology and Systems (ICWITS), Maui, Hawaii, USA, pp. 1-4, 11-16 Nov. 2012.
    doi:10.1109/ICWITS.2012.6417819