ASTF: Visual Abstractions of Time-Varying Patterns in Radio Signals

作者：Ying Zhao, Luhao Ge, Huixuan Xie, Genghuai Bai, Zhao Zhang, Qiang Wei, Yun Lin, Yuchao Liu, Fangfang Zhou · 发表于：IEEE Transactions on Visualization and Computer Graphics · 年份：2022 · DOI：10.1109/tvcg.2022.3209469 · 被引用次数：33 · 研究领域：Data Visualization and Analytics、Time Series Analysis and Forecasting、Music and Audio Processing

A time-frequency diagram is a commonly used visualization for observing the time-frequency distribution of radio signals and analyzing their time-varying patterns of communication states in radio monitoring and management. While it excels when performing short-term signal analyses, it becomes inadaptable for long-term signal analyses because it cannot adequately depict signal time-varying patterns in a large time span on a space-limited screen. This research thus presents an abstract signal time-frequency (ASTF) diagram to address this problem. In the diagram design, a visual abstraction method is proposed to visually encode signal communication state changes in time slices. A time segmentation algorithm is proposed to divide a large time span into time slices. Three new quantified metrics and a loss function are defined to ensure the preservation of important time-varying information in the time segmentation. An algorithm performance experiment and a user study are conducted to evaluate the effectiveness of the diagram for long-term signal analyses.