ASTF: Visual Abstractions of Time-Varying Patterns in Radio Signals
September 30, 2022 Β· Declared Dead Β· π IEEE Transactions on Visualization and Computer Graphics
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Authors
Ying Zhao, Luhao Ge, Huixuan Xie, Genghuai Bai, Zhao Zhang, Qiang Wei, Yun Lin, Yuchao Liu, Fangfang Zhou
arXiv ID
2209.15223
Category
eess.SP: Signal Processing
Cross-listed
cs.HC
Citations
35
Venue
IEEE Transactions on Visualization and Computer Graphics
Last Checked
6 months ago
Abstract
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.
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