학술논문

ECA-MURE Algorithm and CRB Analysis for High-Precision DOA Estimation in Coprime Sensor Arrays
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
Sensors
Sensor arrays
Manifolds
Covariance matrices
Eigenvalues and eigenfunctions
Signal processing
Sensor systems
coprime array
direction-of-arrival (DOA) estimation
manifold reconstruction
sensor array
signal processing
unitary ESPRIT
Language
ISSN
2475-1472
Abstract
The enhanced coprime array (ECA), in conjunction with the manifold reconstruction unitary ESPRIT (MURE) algorithm, offers a groundbreaking solution for direction-of-arrival (DOA) estimation in coprime sensor arrays. Coprime arrays, known for their ability to capture signals from multiple uncorrelated sources, present unique challenges due to their nonstandard geometry. The MURE algorithm seamlessly combines manifold reconstruction and unitary ESPRIT techniques to address these challenges. One significant contribution of this research is the Cramér–Rao Bound (CRB) analysis, shedding light on the fundamental limits of DOA estimation in coprime arrays. In addition, a comprehensive computational complexity analysis provides insights into the algorithm's efficiency. Extensive computer simulations consistently demonstrate the superior performance of the ECA-MURE algorithm, showcasing its accuracy and robustness. This innovative approach has far-reaching implications for applications relying on precise DOA estimation, including radar systems, wireless communication, and acoustic sensing. ECA-MURE unlocks the potential of coprime arrays, making them more practical and effective in real-world scenarios.