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

TL;DR

This paper introduces the ASTF diagram, a visual abstraction technique for effectively representing long-term time-varying patterns in radio signals, overcoming limitations of traditional time-frequency diagrams.

Contribution

It proposes a novel visual abstraction method, a time segmentation algorithm, and new metrics to preserve important signal information over extended periods.

Findings

The ASTF diagram effectively visualizes long-term radio signal patterns.

The proposed segmentation algorithm accurately captures signal state changes.

User studies confirm improved analysis of long-term signal data.

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.