A method for source number estimation with density-based clustering algorithm

Abstract

Almost all high-performance spatial spectrum estimation algorithms for direction of arrival (DOA) estimation are based on accurate source number estimation. Applied with features of covariance matrix eigenvalues of received data and compared with commonly-used K-means algorithm, this article proposes to use a density-based clustering algorithm, which is ordering points to identify the clustering structure (OPTICS) and its detailed steps, to estimate the accurate source number. The experimental results applying with OPTICS algorithm demonstrate better performance on source number estimation over other algorithms under the same conditions.