A System for Data Fusion of Multi-Source Wireless Monitoring Devices and Identification of Illegal FM Broadcast Signals

In response to the escalating development of wireless monitoring devices and system platforms by radio regulatory authorities across the nation, the imperative for an efficient and secure data fusion platform has emerged. This platform facilitates the integration and sharing of diverse information from domestic and international wireless monitoring devices, fostering cross-domain and cross-system collaboration. It not only standardizes data and protocols but also optimizes resource utilization, enhances efficiency, and ensures data security and privacy. Simultaneously, the routine monitoring of frequency modulation broadcast spectrum and the crackdown on illegal activities, such as unauthorized “pirate radio” stations, have become integral components of radio regulatory work. Addressing the challenges of current data fusion platforms, including differences in standards, data security, and data diversity, we propose a comprehensive system for wireless monitoring devices. Leveraging innovative atomization concepts and the efficient JavaSSM framework, our system modularizes data processing and service validation tasks, ensuring reliability and stability in practical operations. Additionally, we introduce a method for monitoring frequency modulation broadcast signals, utilizing template-based comparisons and speech-to-text keyword matching algorithms. This approach aims to identify illegal signals, including “pirate radio”, by evaluating spectrum thresholds and conducting comparisons with a secure signal library. The system further employs speech-to-text operations and keyword matching for the detection of illicit broadcast content. Our research contributes to the evolving field of wireless monitoring, providing a robust solution for the identification and prevention of unauthorized broadcasts.