Sparsity-Based MIMO Radars
From MaRDI portal
Publication:5020143
DOI10.1007/978-3-030-69637-5_17zbMath1479.94053OpenAlexW3197290397MaRDI QIDQ5020143
Azra Abtahi, Farokh A. Marvasti
Publication date: 4 January 2022
Published in: Applied and Numerical Harmonic Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-030-69637-5_17
Sampling theory, sample surveys (62D05) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Sampling theory in information and communication theory (94A20)
Cites Work
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Iterative thresholding for sparse approximations
- Analysis of sparse MIMO radar
- CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
- Spectral compressive sensing
- The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
- Atomic Decomposition by Basis Pursuit
- On Probing Signal Design For MIMO Radar
- Bayesian Compressive Sensing
- Block-Sparse Signals: Uncertainty Relations and Efficient Recovery
- Sensitivity to Basis Mismatch in Compressed Sensing
- Recovery of Sparse Translation-Invariant Signals With Continuous Basis Pursuit
- Target Estimation Using Sparse Modeling for Distributed MIMO Radar
- Measurement Matrix Design for Compressive Sensing–Based MIMO Radar
- Adaptive Strategies for Target Detection and Localization in Noisy Environments
- Frequency-Hopping Code Design for MIMO Radar Estimation Using Sparse Modeling
- Robustly Stable Signal Recovery in Compressed Sensing With Structured Matrix Perturbation
- Perturbed Orthogonal Matching Pursuit
- Matrix Completion in Colocated MIMO Radar: Recoverability, Bounds & Theoretical Guarantees
- Joint Sparse Recovery Method for Compressed Sensing With Structured Dictionary Mismatches
- Semidefinite Programming for Computable Performance Bounds on Block-Sparsity Recovery
- Regression Shrinkage and Selection via The Lasso: A Retrospective
- Robust Recovery of Signals From a Structured Union of Subspaces
- Sparse Signal Processing
- Distilled Sensing: Adaptive Sampling for Sparse Detection and Estimation
- Analysis of Orthogonal Matching Pursuit Using the Restricted Isometry Property
- A sparse signal reconstruction perspective for source localization with sensor arrays
- L2-Regularized Iterative Weighted Algorithm for Inverse Scattering
- Model Selection and Estimation in Regression with Grouped Variables
