Abstract
The wideband direction of arrival (DOA) estimation problem can be formulated into a narrowband form by applying discrete Fourier Transform (DFT) to sensor measurements; however, a large number of temporal snapshots are required in order to meet the narrowband assumption in the frequency-domain. To reduce the number of snapshots required, a convolutional sparse coding (CSC) based wideband signal model is proposed for direct time-domain DOA estimation, and a group sparsity based minimization problem is formulated. Simulation results indicate that the proposed time-domain CSC (TD-CSC) based method has a better performance than the frequency-domain method, but with a higher computational complexity.
| Original language | English |
|---|---|
| Pages (from-to) | 274-278 |
| Number of pages | 5 |
| Journal | IEEE Signal Processing Letters |
| Volume | 29 |
| DOIs | |
| Publication status | Published - Dec 2021 |
Keywords
- Convolution
- Direction-of-arrival estimation
- Discrete Fourier transforms
- Estimation
- Narrowband
- Time-domain analysis
- Wideband
ASJC Scopus subject areas
- Signal Processing
- Applied Mathematics
- Electrical and Electronic Engineering
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