Intelligent Upgrading of the Localized GNSS Monitoring System: Profound Integration of Blockchain and AI

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Udgivet i:Electronics vol. 14, no. 3 (2025), p. 490
Hovedforfatter: Lu, Tianzeng
Andre forfattere: Sun, Yanan, Zhu, Qinglin, Zhou, Xiaolin, Li, Qiaoyang, Liu, Jianan
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MDPI AG
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035 |a 3165771111 
045 2 |b d20250101  |b d20251231 
084 |a 231458  |2 nlm 
100 1 |a Lu, Tianzeng  |u China Research Institute of Radiowave Propagation, No. 36 Xianshan East Road, Chengyang District, Qingdao 266107, China; <email>lutz@crirp.ac.cn</email> (T.L.); <email>l18211157827@126.com</email> (J.L.) 
245 1 |a Intelligent Upgrading of the Localized GNSS Monitoring System: Profound Integration of Blockchain and AI 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a With the extensive application of the Global Navigation Satellite System (GNSS), the intelligent upgrading of the GNSS monitoring system is of particular significance. Traditional GNSS monitoring systems typically rely on a centralized architecture, which possesses certain drawbacks when it comes to data tampering, fault tolerance, and data sharing. This paper presents an intelligently upgraded localized GNSS monitoring system that integrates blockchain and artificial intelligence (AI) technology to achieve the deep integration of security, transparency, and intelligent processing of monitoring data. Firstly, this paper employs blockchain technology to guarantee the integrity and tamper-resistance of GNSS monitoring data and utilizes a distributed ledger structure to realize the decentralization of data storage and transmission, thereby enhancing the anti-attack capability and reliability of the system. Secondly, the LSTM model is utilized to analyze and predict the vast amount of monitoring data in real-time, enabling the intelligent detection of GNSS signal anomalies and deviations and providing real-time early warnings to optimize the monitoring effect. Based on this architecture, we also combine the trained model with smart contracts to realize real-time monitoring and early warnings of GNSS satellites. By integrating the security guarantee of blockchain and the intelligent analysis ability of AI, the localized GNSS monitoring system can offer more efficient and accurate data monitoring and management services. In the study, we constructed a prototype system and tested it in both simulated and real environments. The results indicate that the system can effectively identify and respond to GNSS signal anomalies, and enhance the monitoring accuracy and response speed. Additionally, the application of blockchain enhances the immutability and traceability of data, providing a solid foundation for the long-term storage and auditing of GNSS data. The introduction of AI algorithms, especially the application of the Long Short-Term Memory (LSTM) network in anomaly detection, has significantly enhanced the system’s ability to recognize complex patterns. 
651 4 |a United States--US 
651 4 |a China 
653 |a Radio communications 
653 |a Receivers & amplifiers 
653 |a Accuracy 
653 |a Location based services 
653 |a Computer architecture 
653 |a Distributed ledger 
653 |a Upgrading 
653 |a Fault tolerance 
653 |a Blockchain 
653 |a Navigation systems 
653 |a Monitoring 
653 |a Monitoring systems 
653 |a Management services 
653 |a Pattern recognition 
653 |a Technology 
653 |a Armed forces 
653 |a Innovations 
653 |a Global positioning systems--GPS 
653 |a Data analysis 
653 |a Data integrity 
653 |a Infrastructure 
653 |a Artificial intelligence 
653 |a National security 
653 |a Algorithms 
653 |a Integrated approach 
653 |a Data storage 
653 |a Anomalies 
653 |a Real time 
653 |a Satellites 
653 |a Cybersecurity 
653 |a Global navigation satellite system 
700 1 |a Sun, Yanan  |u School of Cyber Engineering, Xidian University, Xi’an 710071, China; <email>23151214093@stu.xidian.edu.cn</email> 
700 1 |a Zhu, Qinglin  |u China Research Institute of Radiowave Propagation, No. 36 Xianshan East Road, Chengyang District, Qingdao 266107, China; <email>lutz@crirp.ac.cn</email> (T.L.); <email>l18211157827@126.com</email> (J.L.) 
700 1 |a Zhou, Xiaolin  |u School of Cyber Engineering, Xidian University, Xi’an 710071, China; <email>23151214093@stu.xidian.edu.cn</email> 
700 1 |a Li, Qiaoyang  |u Xi’an Aeronautics Computing Technique Research Institute, Aviation Industry Corporation of China, Xi’an 710065, China; <email>qiaoyangli222@126.com</email> 
700 1 |a Liu, Jianan  |u China Research Institute of Radiowave Propagation, No. 36 Xianshan East Road, Chengyang District, Qingdao 266107, China; <email>lutz@crirp.ac.cn</email> (T.L.); <email>l18211157827@126.com</email> (J.L.) 
773 0 |t Electronics  |g vol. 14, no. 3 (2025), p. 490 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3165771111/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
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