TY - GEN
T1 - Direction-of-Arrival Estimation for Constant Modulus Signals via Convex Optimization
AU - Wu, Xunmeng
AU - Yang, Zai
AU - Xu, Zongben
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Several man-made signals in communications and array processing, e.g., phase-modulated and frequency-modulated signals, exhibit the constant modulus (CM) property. This paper is concerned about the problem of direction-of-arrival (DOA) estimation for CM source signals using linear arrays. Existing methods either rely on nonconvex optimization suffering from convergence or optimality issues or cannot fully use the CM property of signals or the array manifold due to great challenges brought by the highly nonconvex CM constraints. In this paper, we propose a convex optimization approach for CM DOA estimation based on atomic norm minimization. Our main contributions are summarized below. 1) To use the CM property, we define a CM atomic norm and formulate the CM DOA estimation problem as an ANM problem. 2) We propose a semidefinite programming, by introducing a series of positive-semidefinite structured matrices, to characterize the CM atomic norm and enable computations of the CM ANM problem. 3) Simulations are carried out that validate the advantageous performance of the proposed approach.
AB - Several man-made signals in communications and array processing, e.g., phase-modulated and frequency-modulated signals, exhibit the constant modulus (CM) property. This paper is concerned about the problem of direction-of-arrival (DOA) estimation for CM source signals using linear arrays. Existing methods either rely on nonconvex optimization suffering from convergence or optimality issues or cannot fully use the CM property of signals or the array manifold due to great challenges brought by the highly nonconvex CM constraints. In this paper, we propose a convex optimization approach for CM DOA estimation based on atomic norm minimization. Our main contributions are summarized below. 1) To use the CM property, we define a CM atomic norm and formulate the CM DOA estimation problem as an ANM problem. 2) We propose a semidefinite programming, by introducing a series of positive-semidefinite structured matrices, to characterize the CM atomic norm and enable computations of the CM ANM problem. 3) Simulations are carried out that validate the advantageous performance of the proposed approach.
UR - https://www.scopus.com/pages/publications/85193841016
U2 - 10.1109/PIERS62282.2024.10618391
DO - 10.1109/PIERS62282.2024.10618391
M3 - 会议稿件
AN - SCOPUS:85193841016
T3 - 2024 Photonics and Electromagnetics Research Symposium, PIERS 2024 - Proceedings
BT - 2024 Photonics and Electromagnetics Research Symposium, PIERS 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 Photonics and Electromagnetics Research Symposium, PIERS 2024
Y2 - 21 April 2024 through 25 April 2024
ER -