| Paper: | SAM-P4.8 | ||
| Session: | Sensor Array Processing | ||
| Time: | Thursday, May 18, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Sensor Array and Multichannel Signal Processing: Source localization, separation, classification, and tracking | ||
| Title: | An Improved Subspace-based Algorithm in the Small Sample Size Regime | ||
| Authors: | Xavier Mestre, Francisco Rubio, Centre Tecnologic de Telecomunicacions de Catalunya (CTTC), Spain | ||
| Abstract: | A new method for subspace identification in array signal processing applications is proposed. The method is based on random matrix theory and provides consistent estimates even when the observation dimension increases without bound at the same rate as the number of observations. This guarantees a good behavior in finite sample size situations, where the number of sensors and the number of samples have the same order of magnitude. Consistency of the algorithm holds in situations where the signal and noise subspaces are asymptotically separable in the sense that, in the asymptotic sample eigenvalue distribution, signal and noise eigenvalues generate different spectral clusters. | ||
©2018 Conference Management Services, Inc. -||- email: webmaster@icassp2006.org -||- Last updated Friday, August 17, 2012