ELEDIA

Seminar by Dr. Yu ZHONG
The ELEDIA Research Center is pleased to announce the seminar entitled "Inversion-Friendly Modelling for Inverse Electromagnetic Scattering Problems" which will…
ELEDIA@AUTH has joined the ELEDIA Research Center Network
The ELEDIA Research Center is very pleased to welcome the ELEDIA@AUTH as part of the ELEDIA Network Labs. ELEDIA@AUTH research…
Prof. Oliveri named Associate Editor of IEEE JMMCT
The ELEDIA Research Center is pleased to announce that Prof. Giacomo Oliveri has been named Associate Editor of the IEEE Journal…
R. J. Mailloux has joined ELEDIA
The ELEDIA Research Center is pleased to announce that Dr. R. J. Mailloux is member of the ELEDIA Teaching Staff.…
 
 
The real-time knowledge of the direction of arrival (DOA) of the signals impinging on an antenna receiver enables the use of adaptive control algorithms suitable for limiting the effects of interferences and improve the performance of the wireless communication system. The use of LBE Algorithms provides high computational efficiency for real-time computing essential in many application scenarios.
   
Mobile wireless communications, time varying scenarios, localization and tracking systems

 

Mobile Communications 

Antenna System Architecture

Planar Antenna Geometry
 

Approaches based on regression and classification have been developed by members of the ELEDIA Research Center exploiting the generalization capabilities of learning by example methodologies like neural networks (NN) and support vector machine (SVM) for the online DOA estimation of single and multiple signals. Multi-resolution strategies have been also suitably defined in order to further increase the performance of the proposed approaches, thus leading to

  1. enhanced angular resolution of the detection process in the region of incidence of the impinging signals;
  2. real-time evaluation of single and multiple DOAs through the definition of probabilities that a signal impinges on the antenna array. Both linear and planar geometries have been investigated;
  3. high robustness in case of noisy data thanks to the generalization capabilities of the adopted methods.

Research activities concerning the DOA estimation have been focused in the mathematical formulation of the training and testing procedures of LBE algorithms. The antenna geometries have been modeled and the corresponding received signals have been defined in order to efficiently evaluate the signal covariance matrix. Moreover, feature selection strategies have been introduced in order to extract as much information as possible from the available data.

Estimated 2-D DOAs
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Keywords: Direction of Arrival Estimation, Learning by Examples, SVM, Mobile Communications


See Also
  • M. Donelli, F. Viani, P. Rocca, and A. Massa, "An innovative multi-resolution approach for DOA estimation based on a support vector classification," IEEE Transactions on Antennas and Propagation, vol. 57, no. 8, pp. 2279-2292, August 2009.
  • L. Lizzi, F. Viani, M. Benedetti, P. Rocca, and A. Massa, "The M-DSO-ESPRIT method for maximum likelihood DoA estimation," Progress in Electromagnetic Research, vol. 80, pp. 477-497, 2008.
  • M. Donelli, R. Azaro, L. Lizzi, F. Viani, and A. Massa, "A SVM-based multi-resolution procedure for the estimation of the DOAs of interfering signals in a communication system," Proc. European Conference on Antennas & Propagation (EuCAP), Nice, France, 6-10 November, 2006.
  • M. Benedetti, P. Rocca, M. Donelli, L. Lizzi, F. Viani, M. Martinelli, L. Ioriatti and A. Massa, "On the integration of smart antennas in wireless sensor networks," Proc. 2008 IEEE AP-S International Symposium, San Diego, USA, July 5-11, 2008.