Enhanced PUMA for DOA estimation

Enhanced PUMA for direction-of-arrival estimation and its performance analysis
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Updated 13 Jun 2018

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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 sources where $P\geq K$, 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.
C. Qian, L. Huang, N. D. Sidiropoulos and H. C. So, "Enhanced PUMA for direction-of-arrival estimation and its performance analysis," IEEE Transactions on Signal Processing, vol.64, no.16, pp.4127-4137, 2016.

Cite As

cheng qian (2025). Enhanced PUMA for DOA estimation (https://uk.mathworks.com/matlabcentral/fileexchange/67710-enhanced-puma-for-doa-estimation), MATLAB Central File Exchange. Retrieved .

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Version Published Release Notes
1.0.0.0

function with a demo