Enhanced PUMA for direction-of-arrival estimation and its performance analysis

Cheng Qian, Lei Huang, Nicholas D. Sidiropoulos, Hing Cheung So

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Direction-of-arrival (DOA) estimation is a problem of significance in many applications. In practice, due to the occurrence of coherent signals and/or when the number of available snapshots is small, it is a challenge to find DOAs accurately. This problem is revisited here through a new enhanced principal-singular-vector utilization for modal analysis (EPUMA) DOA estimation approach, which improves the threshold performance by first generating (P+K) DOA candidates for K sources where P ≥ K, and then judiciously selecting K of them. The asymptotic variance of EPUMA is theoretically derived, and numerical results are provided to validate the asymptotic analysis and illustrate the practical merits of EPUMA.

Original languageEnglish (US)
Article number7435323
Pages (from-to)4127-4137
Number of pages11
JournalIEEE Transactions on Signal Processing
Volume64
Issue number16
DOIs
StatePublished - Aug 15 2016

Keywords

  • DOA estimation
  • linear prediction
  • small sample size
  • subspace method
  • weighted least squares

Fingerprint Dive into the research topics of 'Enhanced PUMA for direction-of-arrival estimation and its performance analysis'. Together they form a unique fingerprint.

Cite this