DOA Based on Manifold Separation Technique and Dimensionality Reduction

Abstract

In this paper, we investigate the high resolution of arbitrary array applied to wireless positioning system and propose a Direction of Arrival (DOA) estimation algorithm based on the Manifold Separation Technique (MST). In order to reduce the error of MST model caused by noise, this algorithm uses the MST to decompose the steering vector into sampling matrix (only describing the array itself) and Vandermonde form (only relating to the direction of arrival), the steering vector of arbitrary array is represented by combining the Effective Aperture Distribution Function (EADF). In order to reduce the complexity of Multiple Signal Classification (MUSIC) algorithm of two-dimensional array, the 2D spectral peak search is decomposed into two one-dimensional spectral peak searches using dimensionality reduction methods. Simulation results show that the algorithm not only reduces the computational complexity, but also has good performance of low signal to noise ratio (SNR).