Name
Abstract | ||
|---|---|---|
This work addresses the problem of direction-of-arrival (DOA) estimation, where true DOAs are not on the sampling grid when sparse signal recovery concept is adopted. To estimate DOAs exploring its sparse property, a basis is usually required. However, off-grid issue persists even when a large basis is constructed. To handle such an off-grid DOAs estimation problem, off-grid problem is remodelled such that it is represented by an offset matrix, which is a sparse matrix. A direct estimate of the offset matrix is developed to compensate the off-grid by utilizing the fact that the offset matrix is a sparse matrix. Through exploring the sparsity of the DOAs and the offset matrix, an approach that simultaneously recover the unknown DOA and offset matrix is presented to achieve final DOA estimation. Numerical studies are presented to demonstrate the effectiveness of the proposed method. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP) | DOA estimation, off-grid, sparsity, iterative |
Field | DocType | Citations |
Pattern recognition,Matrix (mathematics),Computer science,Signal recovery,Artificial intelligence,Sampling (statistics),Grid,Offset (computer science),Sparse matrix | Conference | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongqing Liu | 1 | 0 | 1.35 |
| Luming Zhao | 2 | 0 | 0.34 |
| Yong Li | 3 | 0 | 0.68 |
| Yi Zhou | 4 | 15 | 9.83 |