How to Classify Signals Using Spectrum Recording

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HandHeld Signal Analyzer
+ HandHeld Signal Analyzer
HandHeld Signal Analyzer
+ HandHeld Signal Analyzer

Capture and Classify Radio Frequency (RF) Signals

Modern RF environments often contain a mix of known, unknown, and intermittent signals that can be difficult to identify in real time, especially when engineers are investigating interference, spectrum violations, or disruptions to mission-critical communications. In these situations, the ability to capture wideband spectrum activity and replay it for deeper analysis is essential for understanding what occurred, when it happened, and how it affected overall system performance. As spectrum environments become more congested and dynamic, engineers need tools that support both real-time awareness and detailed post-capture investigation.

By combining spectrum recording from Keysight FieldFox Handheld Signal Analyzers with Keysight Spectrum Management Software, engineers can classify signals after capture, correlate events over time, and distinguish expected transmissions from anomalous emitters using advanced visualization and analysis workflows. This approach enables more thorough investigation of complex RF events, improves the ability to identify intermittent or hard-to-catch signals, and supports more confident decision-making during troubleshooting, spectrum monitoring, and operational analysis.

Signal Classification with Recording Solution

Field spectrum investigation often requires engineers to record wideband RF activity and capture IQ data at the point of occurrence so intermittent, unknown, or difficult-to-observe signals can be analyzed later in greater detail. Keysight’s FieldFox Handheld Spectrum Analyzers support this workflow by enabling direct field capture of real-world spectrum activity, while Keysight Spectrum Management Software adds advanced post-processing, visualization, and signal classification capabilities for deeper analysis. Together, they provide a comprehensive workflow for identifying unknown signals, analyzing interference patterns, correlating events over time, and distinguishing expected transmissions from anomalous emitters, helping accelerate RF decision-making from field to lab and improving confidence in troubleshooting, spectrum monitoring, and mission-critical operational analysis.
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Block Diagram of Signal Classification with Recording Solution

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