Abstract
Direction-of-arrival (DOA) estimation involves the
localization of a few sources from a limited number of observations
on an array of sensors. Thus, DOA estimation can
be formulated as a sparse signal reconstruction problem and
solved efficiently with compressive sensing (CS) to achieve highresolution
imaging. Utilizing the dual optimal variables of the CS
optimization problem, it is shown with Monte Carlo simulations
that the DOAs are accurately reconstructed through polynomial
rooting (Root-CS). Polynomial rooting is known to improve the
resolution in several other DOA estimation methods. However,
traditional methods involve the estimation of the cross-spectral
matrix hence they require many snapshots and stationary incoherent
sources and are suitable only for uniform linear arrays
(ULA). Root-CS does not have these limitations as demonstrated
on experimental towed array data from ocean acoustic measurements.
Original language | English |
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Title of host publication | Proceedings of IEEE International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing |
Number of pages | 5 |
Publisher | IEEE |
Publication date | 2015 |
Article number | 7330273 |
ISBN (Print) | 9781479974207 |
DOIs | |
Publication status | Published - 2015 |
Event | 2015 3rd International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing - Pisa, Italy Duration: 17 Jun 2015 → 19 Jun 2015 Conference number: 3 https://ieeexplore.ieee.org/xpl/conhome/7312392/proceeding |
Workshop
Workshop | 2015 3rd International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing |
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Number | 3 |
Country/Territory | Italy |
City | Pisa |
Period | 17/06/2015 → 19/06/2015 |
Internet address |