Signal detection is a fundamental task in various fields like radar, sonar, communication systems, and medical imaging. It involves deciding whether a desired signal is present in a noisy environment. The covariance matrix, which captures the statistical properties of the noise, plays a crucial role in designing optimal detection algorithms. However, in many practical scenarios, the covariance matrix is unknown due to factors like limited data, non-stationary noise, or complex environments. This unknown covariance matrix presents significant challenges for signal detection.
Signal detection is a fundamental task in various fields like radar, sonar, communication systems, and medical imaging. It involves deciding whether a desired signal is present in a noisy environment. The covariance matrix, which captures the statistical properties of the noise, plays a crucial role in designing optimal detection algorithms. However, in many practical scenarios, the covariance matrix is unknown due to factors like limited data, non-stationary noise, or complex environments. This unknown covariance matrix presents significant challenges for signal detection.
