A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method
AbstractInterferences 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
Scifeed alert for new publicationsNever 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
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.
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(3):329.Chicago/Turabian Style
Li, Wutao; Huang, Zhigang; Lang, Rongling; Qin, Honglei; Zhou, Kai; Cao, Yongbin. 2016. "A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method." Sensors 16, no. 3: 329.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.