Title :
Adaptive re-weighting homotopy for sparse beamforming
Author :
Neto, Fernando G. A. ; Nascimento, Vitor H. ; Zakharov, Yuriy V. ; de Lamare, Rodrigo C.
Author_Institution :
Escola Politec., Univ. of Sao Paulo, Sao Paulo, Brazil
Abstract :
In this paper, a complex adaptive re-weighting algorithm based on the homotopy technique is developed and used for beamforming. A multi-candidate scheme is also proposed and incorporated into the adaptive re-weighting homotopy algorithm to choose the regularization factor and improve the signal-to-interference plus noise (SINR) performance. The proposed algorithm is used to minimize the degradation caused by sparsity in arrays with faulty sensors, or when the required degrees of freedom to suppress interference is significantly less than the number of sensors. Simulations illustrate the algorithm´s performance.
Keywords :
array signal processing; interference suppression; sensors; SINR performance; adaptive reweighting homotopy algorithm; complex adaptive reweighting algorithm; degree of freedom; faulty sensors; interference suppression; multicandidate scheme; regularization factor; signal-to-interference plus noise performance; sparse beamforming; Array signal processing; Interference; Sensor arrays; Signal processing algorithms; Signal to noise ratio; Vectors; Multi-candidate re-weighting homotopy; adaptive algorithms; beamforming;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon