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Sparsity-based direction-of-arrival estimation for strictly non-circular sources

: Steinwandt, Jens; Römer, Florian; Haardt, Martin


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society:
IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016. Proceedings : March 20-25, 2016, Shanghai International Convention Center, Shanghai, China
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-4799-9988-0 (electronic)
ISBN: 978-1-4799-9987-3 (USB)
ISBN: 978-1-4799-9989-7 (print)
International Conference on Acoustics, Speech and Signal Processing (ICASSP) <2016, Shanghai>
Conference Paper
Fraunhofer IIS ()
Richtungsschätzung (DoA)

Direction of arrival (DOA) estimation via sparse signal recovery (SSR) has recently attracted a considerable research interest due to its various advantages over the conventional DOA estimation methods. Yet, the performance of the SSR-based algorithms can be further enhanced by exploiting the structure of strictly non-circular (NC) signals. In this paper, we present a novel strategy to take the NC signal structure into account for the SSR, which results in a two-dimensional SSR problem. Thereby, the known benefits associated with NC sources can be achieved. Moreover, we address the 2-D off-grid problem by proposing a low-complexity procedure that estimates the sources' grid offset from the closest neighboring grid points. For a single off-grid source, we show analytically that the 2-D offset estimation problem is separable, allowing to perform the offset estimation in both dimensions independently.