APRIL 18-21, 2017
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Multilevel Visual Analysis of Multivariate Radio Signal Data
Radio signal is an essential part in wireless communication, which can shed lights on various communication patterns. In previous works, its temporal and frequency-domain features have been thoroughly studied. But the multivariate features were not fully explored. In this work, we develop a visual analytic system to facilitate multilevel and multivariate analysis towards large scale radio signal data. Our system tightly integrates data analysis in time, frequency and multivariate domains. Specifically, it promotes attribute-based analysis and subspace feature mining using multivariate visualization techniques. It also promotes large scale signal data analysis by multilevel visual designs and database techniques. We demonstrate the effectiveness of our system by a use case with real-world signal data.