Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

Study on Measurement of Group Delay in Broadband Channel Based on Nonlinear Fitting

Authors
Xinfeng Mao, Hong Ma, Ge Song, Baotong Peng
Corresponding Author
Xinfeng Mao
Available Online November 2016.
DOI
https://doi.org/10.2991/aiea-16.2016.17How to use a DOI?
Keywords
Group delay; Fitting; Broadband channel; PCAL.
Abstract

In VLBI, obtaining group delay characteristics of equipment is essential to ensure the measurement accuracy. The thesis proposes a new measurement method, nonlinear fitting method, by analyzing how to get group delay characteristics with direct phase difference method and linear-least-squares fitting method. The result of simulation shows that the method measure group delay two orders of magnitude is more accurate than difference method. Actual data demonstrates that difference method and linear fitting method lose effectiveness in frequency from 270MHz to 370MHz. Otherwise, the nonlinear fitting method's measurement precision of group delay is better than 0.1ns.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
978-94-6252-270-1
ISSN
2352-538X
DOI
https://doi.org/10.2991/aiea-16.2016.17How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xinfeng Mao
AU  - Hong Ma
AU  - Ge Song
AU  - Baotong Peng
PY  - 2016/11
DA  - 2016/11
TI  - Study on Measurement of Group Delay in Broadband Channel Based on Nonlinear Fitting
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 91
EP  - 98
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.17
DO  - https://doi.org/10.2991/aiea-16.2016.17
ID  - Mao2016/11
ER  -