Abstract
Classic source number detection methods, such as Akaike information criterion (AIC) and minimum description length (MDL) need eigenvalue decomposition with more computation and snapshots. For engineering implementation, based on the source number detection method using the traditional Gram-Schmidt (GS) algorithm for estimating original data, a source number detection method using the GS algorithm is proposed, aiming at the covariance matrix and a novel adaptive threshold is obtained. Simulation results show that the method decreases the performance a little, but highly decreases the computation and snapshots compared with AIC and MDL algorithms. Meanwhile, compared with the traditional GS algorithm aiming at original data, the computation is not increased but the performance is obviously improved.
Original language | English |
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Pages (from-to) | 22-25 |
Number of pages | 4 |
Journal | Shuju Caiji Yu Chuli/Journal of Data Acquisition and Processing |
Volume | 21 |
Issue number | SUPPL. |
Publication status | Published - Dec 2006 |
Keywords
- Covariance matrix
- Gram-Schmidt
- Orthography projection
- Source number estimation