A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations
نویسندگان
چکیده
منابع مشابه
A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations
In this paper we address the problem of off-grid direction of arrival (DOA) estimation based on sparse representations in the situation of multiple measurement vectors (MMV). A novel sparse DOA estimation method which changes MMV problem to SMV is proposed. This method uses sparse representations based on weighted eigenvectors (SRBWEV) to deal with the MMV problem. MMV problem can be changed to...
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In this paper, off-grid DOA estimation based on sparse representation and Rife algorithm is presented to improve performance when the sparse signal directions are not on the predefined angular grids. The algorithm is divided into two steps. Firstly, the real-valued sparse representation of array covariance vector (RV-SRACV) algorithm is used to do off-grid DOA estimation, and it does not need t...
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Sparse Bayesian learning (SBL) is applied to the coprime array for underdetermined wideband direction of arrival (DOA) estimation. Using the augmented covariance matrix, the coprime array can achieve a higher number of degrees of freedom (DOFs) to resolve more sources than the number of physical sensors. The sparse-based DOA estimation can deteriorate the detection and estimation performance be...
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Spatial compressive sensing (SCS) has recently been applied to direction-of-arrival (DOA) estimation owing to advantages over conventional ones. However the performance of compressive sensing (CS)-based estimation methods decreases when true DOAs are not exactly on the discretized sampling grid. We solve the off-grid DOA estimation problem using the deterministic maximum likelihood (DML) estima...
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ژورنال
عنوان ژورنال: Sensors
سال: 2015
ISSN: 1424-8220
DOI: 10.3390/s151129721