Performance Analysis of Direction of Arrival Estimation Based on Deep Learning

Chen，Min1; Mao，Xingpeng2; Gong，Yi3

10.1145/3408127.3408156

2020-06-19

ACM International Conference Proceeding Series

228-233

In this paper, a new efficient direction of arrival (DOA) estimation approach based on the deep neural networks (DNN) is proposed, in which a nonlinear mapping that relates the outputs of the receiving antennas with its associated DOA is learning by using the DNN-based network. The novel network architecture is divided into two stages, the detection phase and the DOA estimation phase. Additional detection network attached in our structure dramatically reduces the size of the training set. It has been shown that the proposed method not only can achieve reasonably high DOA estimation accuracy, but also can reduce the computational complexity required by traditional superresolution DOA estimation algorithms such as multiple signal classification (MUSIC). The computer simulation results are performed to investigate the generalization and effectiveness of the proposed approach in different scenarios.

deep neural networks (DNN) Detection network direction of arrival (DOA) estimation network

第一

英语

EI

20204009257794

Multiple signal classification ; Network architecture ; Direction of arrival ; Receiving antennas

Ergonomics and Human Factors Engineering:461.4 ; Information Theory and Signal Processing:716.1

2-s2.0-85091586813

Scopus

1.School of Electronics and Information Engineering,Harbin Institute of Technology,Shenzhen Engineering Laboratory of Intelligent Information Processing for IoT,Southern University of Science and Technology,Harbin,China
2.School of Electronics and Information Engineering,Harbin Institute of Technology,Key Laboratory of Marine Environment Monitoring and Information Processing,Ministry of Industry and Information Technology,Harbin,China
3.Shenzhen Engineering Laboratory of Intelligent Information Processing for IoT,Southern University of Science and Technology,Shenzhen,China

Chen，Min,Mao，Xingpeng,Gong，Yi. Performance Analysis of Direction of Arrival Estimation Based on Deep Learning[C],2020:228-233.