Abstract
Detecting the presence of a signal embedded in noise from a multi-sensor system is a fundamental problem in signal and array processing. In this paper we consider the case where the noise covariance matrix is arbitrary and unknown but we are given both signal bearing and noise-only samples. Using a matrix perturbation approach, combined with known results on the eigenvalues of inverse Wishart matrices, we study the behavior of the largest eigenvalue of the relevant covariance matrix, and derive an approximate expression for the detection probability of Roy's largest root test. The accuracy of our expressions is confirmed by simulations.
| Original language | English |
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| Pages (from-to) | 681-684 |
| Number of pages | 4 |
| Journal | 2011 Ieee Statistical Signal Processing Workshop (Ssp) |
| State | Published - 2011 |
| Event | IEEE Statistical Signal Processing Workshop (SSP) - Nice, FRANCE Duration: 28 Jun 2011 → 30 Jun 2011 |