Low complex direction of arrival estimation method based on adaptive filtering algorithm

Low complex direction of arrival estimation method based on adaptive filtering algorithm

Conventional subspace decomposition-based direction of arrival (DOA) estimation methods require eigenvalue decomposition of spatial covariance matrix, therefore these methods are computationally intensive, and their implementation is difficult in real-time applications. However, a DOA estimation met...

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Bibliographic Details
Main Authors: Babur Jalal, Xiaopeng Yang, Denis Igambi, Tehseen Ul Hassan, Zeeshan Ahmad
Format: Article
Language:English
Published: Wiley 2019-07-01
Series:The Journal of Engineering
Subjects:
eigenvalues and eigenfunctions
adaptive filters
covariance matrices
least mean squares methods
direction-of-arrival estimation
conventional subspace decomposition-based direction
arrival estimation method
eigenvalue decomposition
spatial covariance matrix
DOA estimation method
fixed step size
mean square algorithm
variable step size LMS algorithm
estimated error signal
low complex direction
adaptive filtering algorithm
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0276

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https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0276

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