VisSpecDic: Visual Analysis of Spectrum Situation Data Based on Density Incremental Clustering

The omnipresence of wireless communication highlights the importance of efficient radio spectrum management. Traditional monitoring, based on spectral analysis, is challenged by diverse and fluctuating signal environments. This research introduces the SpecVis system, featuring a Density Incremental Clustering (DIC) algorithm that integrates spectral and signal data for enhanced radio spectrum analysis. The DIC algorithm classifies signal data across frequency and bandwidth grids, using density peaks to identify signal locations and a filtering process to minimize noise interference. It also employs connectivity ratios to discern between fleeting and stable signals. The SpecVis system was evaluated within the FM broadcast band, accurately detecting all authorized signals and offering clear visualizations of signal power and time-frequency dynamics. This system represents a novel approach to real-time spectrum monitoring by combining spectral and signal data analysis. Future enhancements will refine algorithm sensitivity and adapt the system for specific monitoring scenarios.