Effective joint DOA-DOD estimation for the coexistence of uncorrelated and coherent signals in massive multi-input multi-output array systems

Abstract This paper deals with the joint direction-of-arrival (DOA) and direction-of-departure (DOD) estimation when the uncorrelated and coherent (i.e., fully correlated) narrowband signals coexist in multiple-input multiple-output (MIMO) array systems. Two new approaches based on weighted subspace...

Full description

Bibliographic Details
Main Authors: Bobin Yao, Zhi Dong, Weiyu Liu
Format: Article
Language:English
Published: SpringerOpen 2018-10-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13634-018-0585-1
Description
Summary:Abstract This paper deals with the joint direction-of-arrival (DOA) and direction-of-departure (DOD) estimation when the uncorrelated and coherent (i.e., fully correlated) narrowband signals coexist in multiple-input multiple-output (MIMO) array systems. Two new approaches based on weighted subspace fitting and oblique projection for two-dimensional direction estimation, i.e., WSFOPDE and improved WSFOPDE, are proposed. In the WSFOPDE approach, the basic procedure includes three stages. First, the DOA of all signals can be directly acquired by minimizing a reduced-dimensional weighted subspace fitting function. Then, the DOA information of uncorrelated signals are discerned by a classifying indicator; and subsequently, their auto-paired transmit steering vectors with respect to DOD information are derived. Finally, via a new Toeplitz-structured oblique projection, an virtual MIMO array data with only coherent signals remaining is constructed to assist the corresponding auto-paired DOD estimation. In order to promote the accuracy of angle estimation, we also design an improved version. It inherits the above basic procedure and, meanwhile, introduces one-dimensional local DOA spectrum searching to refine the DOA-DOD estimation. Compared with some existing strategies, WSFOPDE and its improved version perform better from the united perspective of computational complexity and estimation accuracy. Numerical simulations verify the advantages and also demonstrate that both can be served as a better alternative to the competitors.
ISSN:1687-6180