Abstract
This letter addresses the problem of signal detection in additive correlated noise whose covariance matrix is Toeplitz. Particularly, we design a novel detection approach in the framework of generalized likelihood ratio test, in which the maximum likelihood (ML) estimate of the Toeplitz covariance matrix is needed. Since there are no closed-form expressions for this ML estimate, we resort to the inverse iterative algorithm. The proposed detector surpasses existing methods in detection power and enjoys the constant false-alarm rate property. Besides, accurate asymptotic null and non-null distributions of the test statistic are derived. Numerical results are presented to validate our theoretical findings.
| Original language | English |
|---|---|
| Article number | 8667717 |
| Pages (from-to) | 813-817 |
| Journal | IEEE Signal Processing Letters |
| Volume | 26 |
| Issue number | 6 |
| Online published | 15 Mar 2019 |
| DOIs | |
| Publication status | Published - Jun 2019 |
Research Keywords
- constant false alarm rate
- generalized likelihood ratio test
- maximum likelihood estimation
- Source detection
- Toeplitz noise covariance