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Target Localization in Multipath Propagation Environment Using Dictionary-Based Sparse Representation
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DOI：10.1109/ACCESS.2019.2947497.png)
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Abstract
En 中文
This paper addresses the target localization problem in complex multipath propagation environment for three-dimensional (3-D) radar systems. Firstly, an approach based on the singular value decomposition (SVD) technique is developed to reduce the data dimension and formulate the joint multiple snapshot sparse representation problem in the signal subspace domain. Subsequently, a novel sparse representation based DOA estimation algorithm, combined with alternatingly iterative and dictionary refinement techniques, is proposed. The Cramr-Rao bounds (CRB) for the target DOA and attenuation coefficient estimations of multipath model are derived in closed forms. Experimental results based on both simulated data and measured data indicate that the target localization accuracy can be effectively enhanced by utilizing the proposed algorithm in complex terrain and/or limited snapshot scenarios.
Keywords:
Radar
Dictionaries
Direction-of-arrival estimation
Sensors
Estimation
Reflection coefficient
Reflection
Cramer-Rao bound (CRB)
direction of arrival (DOA) estimation
parameterized dictionary refinement
multipath propagation
sparse representation
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3.6
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