Next Article in Journal
Modeling the Insertion Mechanics of Flexible Neural Probes Coated with Sacrificial Polymers for Optimizing Probe Design
Previous Article in Journal
A Digitalized Gyroscope System Based on a Modified Adaptive Control Method
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(3), 329; doi:10.3390/s16030329

A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method

1
School of Electronics and Information Engineering, Beihang University, Beijing 100191, China
2
Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China
3
Realsil Microelectronics Inc., Suzhou 215021, China
*
Author to whom correspondence should be addressed.
Academic Editor: Assefa M. Melesse
Received: 22 December 2015 / Revised: 24 January 2016 / Accepted: 29 January 2016 / Published: 4 March 2016
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [1959 KB, uploaded 4 March 2016]   |  

Abstract

Interferences can severely degrade the performance of Global Navigation Satellite System (GNSS) receivers. As the first step of GNSS any anti-interference measures, interference monitoring for GNSS is extremely essential and necessary. Since interference monitoring can be considered as a classification problem, a real-time interference monitoring technique based on Twin Support Vector Machine (TWSVM) is proposed in this paper. A TWSVM model is established, and TWSVM is solved by the Least Squares Twin Support Vector Machine (LSTWSVM) algorithm. The interference monitoring indicators are analyzed to extract features from the interfered GNSS signals. The experimental results show that the chosen observations can be used as the interference monitoring indicators. The interference monitoring performance of the proposed method is verified by using GPS L1 C/A code signal and being compared with that of standard SVM. The experimental results indicate that the TWSVM-based interference monitoring is much faster than the conventional SVM. Furthermore, the training time of TWSVM is on millisecond (ms) level and the monitoring time is on microsecond (μs) level, which make the proposed approach usable in practical interference monitoring applications. View Full-Text
Keywords: global navigation satellite system; interference monitoring; twin support vector machine global navigation satellite system; interference monitoring; twin support vector machine
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Li, W.; Huang, Z.; Lang, R.; Qin, H.; Zhou, K.; Cao, Y. A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method. Sensors 2016, 16, 329.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top