Abstract
Super-nested arrays are receiving growing attention due to their large degrees of freedom (DoF) and the reduced mutual coupling between the array elements. The array has been proposed for one-dimensional direction of arrival (1D-DoA) estimation and is a potential candidate for two-dimensional (2D-DoA) estimation. In this paper, a new 2D super-nested array (2DSNA) is proposed by combining two parallel super-nested arrays spaced by λ/2. The analytical expressions for the second-order and fourth-order difference coarrays are derived. The work also shows that the second-order and fourth-order difference coarrays are hole-free. The proposed configuration has lower mutual coupling effect due to super-nested structure and large DoF. Furthermore, simulation results validate the robustness and accuracy of the DOA estimation performance with the proposed configuration.
| Original language | English |
|---|---|
| Title of host publication | 2024 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2024 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 507-511 |
| Number of pages | 5 |
| ISBN (Electronic) | 9798350309485 |
| DOIs | |
| State | Published - 2024 |
| Event | 2024 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2024 - Madrid, Spain Duration: 8 Jul 2024 → 11 Jul 2024 |
Publication series
| Name | 2024 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2024 |
|---|
Conference
| Conference | 2024 IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2024 |
|---|---|
| Country/Territory | Spain |
| City | Madrid |
| Period | 8/07/24 → 11/07/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- 2D-DoA estimation
- 2DSNA
- difference coarray
- fourth-order statistics
- second-order statistics
- super-nested array
ASJC Scopus subject areas
- Computer Networks and Communications
- Signal Processing
- Information Systems and Management
- Control and Optimization
- Modeling and Simulation