Joint DOA and Frequency Estimation With Sub-Nyquist Sampling in the Sparse Array System

Several array systems along with algorithms based on sub-Nyquist sampling techniques have been extensively studied. This letter is committed to the joint frequency and direction-of-arrival estimation of more sources than sensors in a subband by using sparse arrays with sub-Nyquist sampling. The newl...

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Bibliographic Details
Published in:IEEE signal processing letters Vol. 25; no. 9; pp. 1285 - 1289
Main Authors: Liu, Liang, Wei, Ping
Format: Journal Article
Language:English
Published: New York IEEE 01.09.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Computer simulation
Covariance matrices
Covariance matrix
Direction of arrival
Direction-of-arrival (DOA) estimation
Direction-of-arrival estimation
Estimation
frequency estimation
IP networks
Sampling
Sensor arrays
Sensors
Signal processing algorithms
sparse array
sub-Nyquist sampling
ISSN:1070-9908, 1558-2361
Online Access:Get full text
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Summary:Several array systems along with algorithms based on sub-Nyquist sampling techniques have been extensively studied. This letter is committed to the joint frequency and direction-of-arrival estimation of more sources than sensors in a subband by using sparse arrays with sub-Nyquist sampling. The newly defined block vectorization eliminates the interference from sub-Nyquist sampling. Based on this, a novel augmented sample covariance matrix method is proposed, which enhances the spatial degrees of freedom and increases the number of identifiable sources. Simulations show that the joint estimation can be realized at a lower sampling rate with fewer sensors at the expense of a degradation in estimation performance. Such an algorithm provides a tradeoff between the expensive resource of sensors and channels, and the estimation performance.
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ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2018.2848838