Fast source number estimation method based on GS orthography projection

Qingchang Tao*, Guigen Huang, Meiguo Gao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

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 languageEnglish
Pages (from-to)22-25
Number of pages4
JournalShuju Caiji Yu Chuli/Journal of Data Acquisition and Processing
Volume21
Issue numberSUPPL.
Publication statusPublished - Dec 2006

Keywords

  • Covariance matrix
  • Gram-Schmidt
  • Orthography projection
  • Source number estimation

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