NDLI: Novel confidence level labelling methods for ADS-B signals with coherent demodulation scheme

Content Provider	IET Digital Library
Author	Ren, Peng Wang, Jianxin Xue, Wen Yang, Shushu Song, Haiwei
Abstract	In the satellite-based application, low signal-to-noise ratio (SNR) is a considerable obstacle for automatic dependent surveillance-broadcast (ADS-B), leading to some erroneous bit declarations. In this case, the confidence level of each bit should be declared legitimately to make full use of error correction. In this study, the authors focus on methods to optimise the confidence declaration for ADS-B signals with coherent demodulation scheme. A novel optimal-threshold labelling method is firstly proposed for known and unknown amplitudes. They also present a dynamic-threshold labelling method, in which a specific threshold is unnecessary. Detailed theoretical analyses are carried out for the proposed methods and are verified by simulations. Finally, they make a comparison between different confidence level labelling methods in terms of reception performance and complexity. A conclusion is set forth that the methods have a high probability of correct reception at low SNRs.
Starting Page	268
Ending Page	278
Page Count	11
ISSN	17518784
Volume Number	14
e-ISSN	17518792
Issue Number	Issue 2, Feb (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/14/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2019.0377
Journal	IET Radar, Sonar & Navigation
Publisher Date	2019-10-24
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	ADS-B Signal Automatic Dependent Surveillance-broadcast Signal Coherent Demodulation Scheme Confidence Level Labelling Method Demodulation Dynamic-threshold Labelling Method Erroneous Bit Declarations Error Correction Low Signal-to-noise Ratio Modulation And Coding Method Optimal-threshold Labelling Method Probability Satellite-based Application Signal Processing Signal Processing And Detection Signal Processing Theory SNR Statistics Surveillance
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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