학술논문

Optimizing Sensor Array DOA Estimation With the Manifold Reconstruction Unitary ESPRIT Algorithm
Document Type
Periodical
Source
IEEE Sensors Letters IEEE Sens. Lett. Sensors Letters, IEEE. 7(12):1-4 Dec, 2023
Subject
Components, Circuits, Devices and Systems
Robotics and Control Systems
Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Direction-of-arrival estimation
Estimation
Manifolds
Sensor arrays
Covariance matrices
Eigenvalues and eigenfunctions
Signal to noise ratio
Sensor signal processing
computational complexity
direction of arrival (DOA) estimation
ESPRIT
manifold reconstruction unitary ESPRIT (MR-UESPRIT)
sensor arrays
Language
ISSN
2475-1472
Abstract
This letter introduces a new algorithm called manifold reconstruction unitary ESPRIT (MR-UESPRIT) for accurately estimating the direction of arrival (DOA). The algorithm combines manifold reconstruction and unitary ESPRIT to overcome the limitations of traditional DOA estimation methods. In this approach, two smaller overlapping subarrays are used to derive a rotational invariance equation, which helps recover the array manifold matrix. As a result, the DOA estimation problem is divided into $K$-individual single-source DOA estimation problems. Each DOA is estimated by minimizing a nonlinear least squares fitting criterion using a computationally efficient Newton's method. Computer simulations are presented to demonstrate the effectiveness of the MR-UESPRIT method compared with standard DOA estimation methods.