Adaptive Beam Forming Algorithm of Anti-Jamming GNSS Terminal Research

Hong Jiao Ma; Meng Li; Kang Wang; Zai Ming He

doi:10.4028/www.scientific.net/AMR.905.591

Paper Titles

The Risks of Data Transmissions in Intrusion and Hold-Up Alarm Systems and Solutions Thereto
p.570

Wireless Sensor Network Based Bridge Health Monitoring System for Long-Span Bridges
p.575

The Signal Timing Method for Roundabout Based on the Constraint of Left-Turn Queue Length
p.580

Unmanned Aerial Vehicle Based Agricultural Remote Sensing Multispectral Image Processing Methods
p.585

Adaptive Beam Forming Algorithm of Anti-Jamming GNSS Terminal Research
p.591

An Energy Efficient Communication Routing Protocol Based on LEACH for WSN
p.595

Analysis and Optimization of Rail Vehicles Networked Control System Based on Static Scheduling Algorithm
p.600

Multiuser Detection with Delay Feedback Scheme for Asynchronous Cooperative Networks
p.611

Research and Implementation on CDR Synthesis Scheme of GTPV2 Protocol in LTE Network
p.615

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 905Adaptive Beam Forming Algorithm of Anti-Jamming...

Adaptive Beam Forming Algorithm of Anti-Jamming GNSS Terminal Research

Abstract:

A variety of high-density and strong signal electromagnetic jamming and interference effect is one of the difficult problems which have bad effects on the accuracy of GNSS Satellite navigation receivers. For different types of jamming and interference effect, this paper will analyze their corresponding coping strategies on GNSS satellite navigation terminal. On the structure basis of the smart antenna array, the algorithm flow of LMS, RLS and CMA are analyzed and the simulation of these three classic beam forming algorithm are also performed. The comparison result of the convergence curves output and convergent beam directional diagram shows that all of them can extract the useful signal from the interfering signals. RLS algorithm has a better setup speed and convergence rate, and also has a strong adaptability to non-stationary signals. Therefore, its filtering performance is significantly better than LMS and CMA. But due to its high computational complexity, real-time processing is very hard to achieve.

You might also be interested in these eBooks

Advances in Applied Materials and Electronics Engineering III

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 905)

Pages:

591-594

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.905.591

Citation:

Cite this paper

Online since:

April 2014

Authors:

Hong Jiao Ma*, Meng Li, Kang Wang, Zai Ming He

Keywords:

Adaptive, Algorithm (GA), Anti-Jamming, GNSS

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Svendsen A S, Gupta I J. Adaptive antenna for handheld GPS receivers [A]. 2010 IEEE/ION Position Location and Navigation Symposium (PLANS) [C]. Indian Wells, CA, USA, 2010. 436-442.

DOI: 10.1109/plans.2010.5507212

Google Scholar

[2] Hu Jia, Huang XiYue. Interference and anti Interference of GPS signal,. Automation and In-strumentation [J]. 2006. 03: 83-87.

Google Scholar

[3] Shen ZiLong. Design and Implementation of Multi-channel interference GPS Receiver [D]. Nanjing University of Science & Technology. (2012).

Google Scholar

[4] A. O'Brien, I J. Gupta. Optimum Adaptive Filtering for GNSS Antenna Arrays [A]. Proceeding of the 21st International Technical Meeting of the Satellite Division of the Institute of Navigation [C]. Savannah, GA, US: The institute of Navigation, 2008: 2796-280.

DOI: 10.33012/2020.17707

Google Scholar

[5] Gong YaoHuan. Adaptive Filter (Time domain adaptive filtering and smart antenna) [M]. The second edition. Beijing: Publishing House of Electronics Industry. (2003).

Google Scholar

[6] A H Sayed. Fundamentals of Adaptive Filtering [M]. Wiley. (2003).

Google Scholar