Binary Radio Tomographic Imaging in Factory Environments Based on LOS/NLOS Identification-Reference-Cited by-同舟云学术

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Binary Radio Tomographic Imaging in Factory Environments Based on LOS/NLOS Identification

Published:2023 Issue: Volume:11 Page:22418-22429
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Matsuda Takahiro¹^ORCID,Nishikawa Yoshiaki¹,Takahashi Eiji²^ORCID,Onishi Takeo²,Takeuchi Toshiki³

Affiliation:

1. Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo, Japan

2. Secure Systems Platforms Research Laboratories, NEC Corporation, Kawasaki, Kanagawa, Japan

3. Advanced Network Research Laboratories, NEC Corporation, Kawasaki, Kanagawa, Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10058967.pdf?arnumber=10058967

Reference48 articles.

1. dRTI

2. Propagation Modeling for Radio Frequency Tomography in Wireless Networks

3. The Detection of Defective Members of Large Populations

4. Enhanced radio tomographic imaging with heterogeneous Bayesian compressive sensing

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Training Data Generation Utilizing LOS Identification for Estimating Spatial Loss Fields;2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring);2023-06

2. Robust Structured Sparsity Based Fused Lasso Estimator With Sensor Position Uncertainty;IEEE Transactions on Circuits and Systems II: Express Briefs;2023

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