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 language | English (US) |
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Article number | 7435323 |
Pages (from-to) | 4127-4137 |
Number of pages | 11 |
Journal | IEEE Transactions on Signal Processing |
Volume | 64 |
Issue number | 16 |
DOIs | |
State | Published - Aug 15 2016 |
Bibliographical note
Publisher Copyright:© 1991-2012 IEEE.
Keywords
- DOA estimation
- linear prediction
- small sample size
- subspace method
- weighted least squares