A Comprehensive Survey on GNSS Interferences and the Application of Neural Networks for Anti-jamming

Abstract

In recent years, modern systems are highly reliant on Global Navigation Satellite Systems (GNSS) as reliable positioning, navigation, and timing services have become crucial in many safety-critical, security, and emergency applications. Although GNSS technology offers precise and global positioning and navigation, the GNSS signals are susceptible to intentional and unintentional Radio Frequency Interferences (RFI) as the signal strength is weak when they reach the receiver. Hence, the receiver's performance gets degraded as the interference signal may cause navigation error or saturate the receiver's operation. Therefore, the research on interference mitigation is of high interest to the GNSS community and is emerging rapidly. In order to have a beneficial and extensive outlook, an in-depth survey on GNSS interferences and the application of metaheuristic based neural networks for interference cancellation has been presented in this paper; with an emphasis on one of the major GNSS threats i.e. jamming. Various solutions adopted by the researchers to cope up with the interference have been surveyed and presented. Also, to have a more intuitive insight, a comparative analysis of the existing mitigating techniques has been summarized. In addition, the review focuses on the neural network approach for anti-jamming and also discusses the implementation strategy of particle swarm optimization based back propagation neural network (PSO-BPNN) to address the shortcomings of traditional training algorithms. Finally, the future aspects to further enhance the neural network algorithms for anti-jamming have also been provided for the benefit of researchers.

KEYWORDS:

• Global Navigation Satellite System (GNSS)
• Jamming
• Navigation
• Neural networks
• Radio frequency interference

Additional information

Notes on contributors

Kambham Jacob Silva Lorraine

K J Silva Lorraine received her BTech (Bachelor of Technology) degree in Electronics and communication engineering from Jawaharlal Nehru Technological University Hyderabad, India, in 2008 and M.E (Master of Engineering) degree in communication engineering from Osmania University, Hyderabad, India, in 2010. She is currently pursuing her PhD from Jawaharlal Nehru Technological University, Kakinada, India. Her research interests include GNSS security, signal processing, and satellite communications. She is an Associate Member of IE and IETE. Corresponding author. Email: [email protected]

Madhu Ramarakula

Madhu Ramarakula received the BE (Bachelor of Engineering) degree in electronics and communication engineering from Osmania University, Hyderabad, India, in 2003 and MTech degree in communication systems from Jawaharlal Nehru Technological University Hyderabad, India, in 2009. He received his PhD degree in electronics and communication engineering from Andhra University, Visakhapatnam, India, in 2014. He is presently working as an assistant professor in the Department of Electronics and Communication Engineering, University College of Engineering Kakinada (A), JNTUK, Kakinada, India. He has 10 years of teaching experience. He has published more than 40 research papers in various reputed national and international journals and conferences. His research interests include mobile and cellular communications, antennas, satellite communications, and GNSS. He is a Member of IEEE. Email: [email protected]