A novel coherence reduction method in compressed sensing for DOA estimation
From MaRDI portal
Publication:2375584
DOI10.1155/2013/548979zbMath1266.94011OpenAlexW2128933678WikidataQ59002996 ScholiaQ59002996MaRDI QIDQ2375584
Xianghua Yao, Feng Lian, Jing Liu, Chongzhao Han
Publication date: 14 June 2013
Published in: Journal of Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2013/548979
Cites Work
- Unnamed Item
- On compressive sensing applied to radar
- Extensions of compressed sensing
- Tracking and data association
- Sparse representations in unions of bases
- Optimized Projections for Compressed Sensing
- Coherence-Based Performance Guarantees for Estimating a Sparse Vector Under Random Noise
- Sparse Channel Estimation for Multicarrier Underwater Acoustic Communication: From Subspace Methods to Compressed Sensing
- Sensitivity to Basis Mismatch in Compressed Sensing
- Structured Compressed Sensing: From Theory to Applications
- Measurement Matrix Design for Compressive Sensing–Based MIMO Radar
- Adaptive Compressed Sensing Radar Oriented Toward Cognitive Detection in Dynamic Sparse Target Scene
- A sparse signal reconstruction perspective for source localization with sensor arrays
- Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ 1 minimization
- Stable signal recovery from incomplete and inaccurate measurements
This page was built for publication: A novel coherence reduction method in compressed sensing for DOA estimation