Performance of the Noise Subspace-Based Estimation Algorithm for Correlated Sources
Enrique A. Santiago, Jiawei Liu, Mohammad Nazmus Saquib · 2018
The NoIse Subspace-based Estimation (NISE) algorithm has been shown to provide adequate direction of arrival (DoA) estimates for uncorrelated sources in traditionally difficult scenarios, with relatively low computational complexity. In this work, we discuss the behavior of NISE in practical scenarios where the sources are correlated, and provide a mathematical proof of its convergence. Numerical results showing the performance of NISE against Unitary Root-MUSIC are also presented.