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Super resolution DOA estimation based on deep neural network

Engineering and Technology

Super resolution DOA estimation based on deep neural network

W. Liu

Discover a groundbreaking deep neural network framework for direction-of-arrival estimation, developed by Wanli Liu, that not only improves resolution but also adapts to various signal conditions. This state-of-the-art approach surpasses previous methodologies and offers remarkable generalization capabilities.

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Playback language: English
Abstract
This paper presents a novel deep neural network (DNN) framework for direction-of-arrival (DOA) estimation that achieves higher resolution and better generalization to random signal numbers and signal-to-noise ratios (SNRs). The proposed DNN outperforms previous methods and reaches the state-of-the-art.
Publisher
Scientific Reports
Published On
Nov 16, 2020
Authors
Wanli Liu
Tags
deep neural network
direction-of-arrival
DOA estimation
signal processing
high resolution
generalization
signal-to-noise ratio

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