Name
Title | ||
|---|---|---|
2D-DOA Estimation in Arc-Array With a DNN Based Covariance Matrix Completion Strategy |
Abstract | ||
|---|---|---|
Two-dimensional direction of arrival (2D-DOA) estimation, or estimating the azimuth and elevation angles of sources simultaneously, is an increasingly important area in array signal processing. This paper presents a 2D-DOA algorithm together with a novel structure of array named Arc-Array (ArcA). The ArcA is enlarged to a virtual Uniform Circular Array (UCA) through a Deep-Neural-Network (DNN) based covariance matrix completion strategy; afterward, the MUSIC algorithm is performed with the completed covariance matrix. The proposed method is named as ArcA-DNN, and the performance of ArcA-DNN is evaluated by computer simulations. The simulation results indicate that the performance of 2D-DOA estimation in ArcA is able to approach that of a complete UCA; meanwhile, the number of physical elements is substantially reduced compared to the UCA. Moreover, the proposed ArcA-DNN algorithm gives access to implementing underdetermined 2D-DOA estimation with reasonable results. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ACCESS.2022.3172478 | IEEE ACCESS |
Keywords | DocType | Volume |
Covariance matrices, Estimation, Antenna arrays, Array signal processing, Signal processing algorithms, Direction-of-arrival estimation, Neurons, 2D-DOA estimation, UCA, ArcA, covariance matrix completion, deep learning | Journal | 10 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ye Tian | 1 | 0 | 1.35 |
| Ruru Mei | 2 | 0 | 0.68 |
| Yonghui Huang | 3 | 2 | 2.81 |
| Xiaogang Tang | 4 | 0 | 0.68 |
| Tianshu Cui | 5 | 0 | 0.34 |