On the DOA Estimation Performance of Optimum Arrays Based on Deep Learning
ID:32
Submission ID:298 View Protection:ATTENDEE
Updated Time:2020-08-05 10:16:59 Hits:477
Oral Presentation
Abstract
In this paper, we investigate the optimality of
deep learning-based optimal sparse arrays in comparison to
well known conventional sparse linear arrays. Recently, a deep
learning-based approach was proposed for antenna selection
purposes as a measure towards reducing high hardware and
computational cost in radar systems. Through numerical examples,
we demonstrated that the proposed approach yields sparse
arrays whose performance and configurations are comparably
closer to conventional sparse arrays.
Keywords
antenna selection; sparse arrays; direction-of-arrival estimation; deep learning
Submission Author
Steven Wandale
Yokohama National University, Japan
Koichi Ichige
Yokohama National University, Japan
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