Enhanced and Generalized Coprime Array for Direction of Arrival Estimation

• Published in: IEEE transactions on aerospace and electronic systems Vol. 59; no. 2; pp. 1327 - 1339
• Main Authors: Shi, Junpeng, Wen, Fangqing, Liu, Yongxiang, Liu, Zhen, Hu, Panhe
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Array signal processing; Arrays; Closed-form solutions; Coprime array; Couplings; Degrees of freedom; Direction of arrival; Direction-of-arrival estimation; Estimation; generic-coarray; Linear arrays; Mutual coupling; Sensor arrays; subspace-based algorithm; uniform degree of freedom (uDOF)
• ISSN: 0018-9251; 1557-9603
• DOI: 10.1109/TAES.2022.3200929

Owing to the large degrees of freedom and reduced mutual coupling by generating difference coarrays, nonuniform linear arrays have aroused great interest in direction of arrival estimation. Previous works have shown some improved sparse arrays, while few find the common features hidden within these structures. In this article, we define a generic-coarray concept to reveal the impacts of variable ranges and element spacing on the uniform degrees of freedom (uDOFs), by which the sufficient condition for the connected coarrays is derived. We then propose an enhanced and generalized coprime array (EGCA) structure from the generic-coarray perspective. We show that the closed-form expression for the range of uDOFs is a function of sensor numbers and interelement spacing. We prove that, by coarray extension and hole filling, the optimized EGCA possesses more uDOFs than the previous coprime arrays. Furthermore, EGCA also provides the minimum number of sensor pairs with small separation. Simulations verify the superiority of EGCA using the subspace-based algorithm.