CRFS, an RF technology company that provides spectrum monitoring, electronic warfare support, geolocation, and signal intelligence solutions for defense and national security applications, offers a Signal Discovery feature in its RFeye DeepView software, designed to help users identify signals of interest within large volumes of captured radio frequency (RF) data.
RFeye DeepView is a forensic signal analysis software used for signal monitoring and measurement. The platform allows users to record and capture RF signals in I/Q data format, which can then be analyzed and processed. After recording terabytes of I/Q data, the Signal Discovery feature enables users to analyze and isolate relevant signals. Monitoring and intercepting signals across wide frequency ranges can present analytical challenges, particularly when signals have complex or low-power characteristics.
How Signal Discovery Works
Modern communication systems often rely on pulses and power characteristics. Signal Discovery provides electronic warfare (EW) and signals intelligence (SIGINT) operators, as well as test engineers, with the ability to analyze pulse parameters in order to identify and potentially geolocate unknown transmissions.
Recording I/Q data over extended periods creates a database of pulse descriptors. This large volume of analog information can be viewed and interpreted statistically using Signal Discovery by identifying hotspots within the dataset.
By querying the database for specific pulse types in real time, users can isolate those signals from the full recording. This allows statistical identification of anomalies by comparing expected and unexpected signal behavior. Users can then zoom into signal patterns, narrowing large datasets from millions of signals to smaller sets for further analysis.
Example: Filtering Signals in a Crowded Wi-Fi Band (2.4 GHz)
Signal Discovery provides a statistical view of signals present in the spectrum. Hovering over signals within the dataset reveals pulse descriptors. The software can display parameters including frequency, time, power, bandwidth, pulse duration, and pulse repetition rate.
Signal hotspot visualization allows users to examine combinations of pulse bandwidth and pulse duration. Selecting a hotspot region can reduce the dataset from approximately 1.4 million signals to 51,722 signals.
Further filtering reveals statistical patterns, reducing the dataset to 1,449 signals. Additional filtering based on statistical parameters can reduce the number further, from 103 signals to 16 signals.
Identifying Patterns in RF Data
Statistical patterns may emerge based on time of day or specific operating periods, which may not be noticeable without the ability to zoom into selected areas of the dataset. Once the number of signals becomes manageable, further analysis can be conducted to identify particular transmitters. While Signal Discovery does not determine signal identity, expected signal types may be inferred within specific frequency bands.
After identifying low-probability-of-intercept (LPI) signals using Signal Discovery, users can analyze them further using RFeye DeepView. If a SIGINT or EW operator or test engineer identifies a signal of interest, a detector can be created for that signal. When the detector is loaded into RFeye Site real-time spectrum monitoring software, it analyzes the signal’s frequency, power, and time characteristics and compares them with a signal library. When a match is found, the system automatically triggers a workflow to geolocate the emitter.
RFeye Ecosystem
Signal Discovery is part of the RFeye ecosystem, which combines RF sensors and software for spectrum monitoring and signal intelligence. RFeye Nodes provide wideband monitoring and real-time signal processing at the edge, while associated software tools support signal detection, recording, geolocation, and post-processing analysis.
The capability supports spectrum monitoring, situational awareness, signal intelligence, and electronic warfare operations in congested electromagnetic environments, including detection of unknown or low signal-to-noise transmissions.
Click here to learn more about the Signal Discovery for RFeye DeepView.
