Bound on the estimation grid size for sparse reconstruction in direction of arrival estimation

Conference paper (2016)

Authors

Coutiño Signal Processing Systems - EEMCS
Pribic Thales
Leus Signal Processing Systems - EEMCS
Research Group
Signal Processing Systems (EEMCS) (TU Delft)
Copyright: © 2016 Mario Coutino, R Pribic, G.J.T. Leus
DOI: https://doi.org/10.1109/ssp.2016.7551781
Compressed sensing Sparse reconstruction Direction of arrival (DOA) estimation Sensing matrix Uniform linear array
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Published Date

25-08-2016

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Signal Processing Systems

Abstract

A bound for sparse reconstruction involving both the signal-to-noise ratio (SNR) and the estimation grid size is presented. The bound is illustrated for the case of a uniform linear array (ULA). By reducing the number of possible sparse vectors present in the feasible set of a constrained ℓ1-norm minimization problem, ambiguities in the reconstruction of a single source under noise can be reduced. This reduction is achieved by means of a proper selection of the estimation grid, which is naturally linked with the mutual coherence of the sensing matrix. Numerical simulations show the performance of sparse reconstruction with an estimation grid meeting the provided bound demonstrating the effectiveness of the proposed bound.

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