Source enumeration in the presence of colored noise

In array signal processing, the detection of the number of sources is an important step. Most approaches assume the signals to be embedded in white noise. However, this assumption is unrealistic in many scenarios. In this letter, we propose a strategy that can handle colored noise. We model the source detection as a regression problem and apply information-theoretic criteria to determine the model order of the regression. We show simulations of different scenarios, where our approach outperforms traditional techniques.

almost cyclostationarity; cycle period estimation; detection; multiple hypothesis test; sample rate conversion

Source enumeration in the presence of colored noise Articles