On the effect of a-priori information on performance of the MDL estimator

Detecting the number of sources is a well known and a well investigated problem. In this problem, the number of sources impinging on an array of sensors is to be estimated. The widely used processor is based on the Minimum Description Length (MDL) criterion where the array is assumed unstructured and the radiating sources are assumed Gaussian. This paper presents an asymptotic analysis of the performance of a different estimator, when some a-priori information is utilized: In particular, the performance of the MDL estimator which assumes Gaussian sources and a structured array when applied to Gaussian sources is analyzed. It is shown that appropriate use of the prior knowledge about the array geometry can lead to significant improvement in the detection performance. Simulation results show good fit between the empirical and the theoretical results.