Paper Info
Title
Data-Driven Passive Localization With Non-Cooperative Radiation Sources via Mutually Inverse Networks.
Abstract
This letter proposes a passive localization method with non-cooperative radiation sources and distributed receivers. In this letter, a pair of mutually inverse networks is put forward. The inverse network aims to generate more labeled data, and the original network is trained with the generated data to learn the mapping from the observed data to the target location. Experimentally, the results sho...
Year
DOI
Venue
2020
10.1109/LCOMM.2020.2968034
IEEE Communications Letters
Keywords
DocType
Volume
Receivers,Training,Training data,Neural networks,Covariance matrices,Task analysis,Base stations
Journal
24
Issue
ISSN
Citations 
4
1089-7798
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Hao Wu19238.83
Yongqiang Cheng213329.99
Hongqiang Wang310623.75