An Array Interpolation Based Compressive Sensing DOA Method for Sparse Array

The CS (Compressive Sensing) DOA (Direction of Arrival) methods usually require large number of sensors and subject to the manifold ambiguity brought by the sparse array. To solve this problem, an array interpolation based compressive sensing DOA method is proposed in this paper. Firstly, multiple s...

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Bibliographic Details
Published in2019 3rd International Conference on Imaging, Signal Processing and Communication (ICISPC) pp. 24 - 27
Main Authors Cui, Ao, Xu, Teng, Yu, Weichuang, He, Peiyu, Xu, Zili
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2019
Subjects
array interpolation
coherent signal
Compressed sensing
compressive sensing
Direction-of-arrival estimation
DOA
Interpolation
Manifolds
Signal to noise ratio
Simulation
sparse array
Sparse matrices
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DOI10.1109/ICISPC.2019.8935709

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Summary:The CS (Compressive Sensing) DOA (Direction of Arrival) methods usually require large number of sensors and subject to the manifold ambiguity brought by the sparse array. To solve this problem, an array interpolation based compressive sensing DOA method is proposed in this paper. Firstly, multiple strategies were applied to interpolate the sparse array with virtual elements to construct a virtual uniform array. Then apply the compressive sensing DOA method on this virtual array to obtain the DOA estimators. Comparing with the actual sparse array, the virtual one has more elements that de-singulars the manifold matrix, which implies satisfaction to the RIP (Restricted Isometry Property) condition. Simulation results demonstrate that our method can achieve DOAs for coherent signals with sparse array under small snapshots and low SNR.
DOI:10.1109/ICISPC.2019.8935709