Sparse and low-rank decomposition of covariance matrix for efficient DOA estimation-Reference-Cited by-同舟云学术

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Sparse and low-rank decomposition of covariance matrix for efficient DOA estimation

Published:2017-05 Issue: Volume: Page:
ISSN:
Container-title:2017 IEEE 9th International Conference on Communication Software and Networks (ICCSN)
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Author:

Chen Yong,Wang Fang,Wan Jianwei,Xu Ke

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8170168/8230062/08230253.pdf?arnumber=8230253

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DOA Estimation via Adaptive Weighted Truncated Nuclear Norm;2023 35th Chinese Control and Decision Conference (CCDC);2023-05-20

2. Wideband DOA estimation via low rank and denoising covariance matrix reconstruction;2022 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC);2022-10-25

3. Adaptive Reconstruction for Spatial Covariance Matrix in Hybrid Massive MIMO Systems;IEEE Access;2021

4. Max-MUSIC: A Low-Complexity High-Resolution Direction Finding Method for Sparse MIMO Radars;IEEE Sensors Journal;2020-12-15

5. Sparse and Low Rank Recovery Based Robust DOA Estimation Method;J ELECTRON INF TECHN;2020

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