RFeye shown on monitor screenThe best monitoring hardware demands the best software and this is it. Everything you need to manage the spectrum in real time, hunt interference, schedule missions, derive actionable intelligence and react to threats. New features and capabilities are added with every release.

Real-time monitoring

RFeye® real-time monitoring software has been designed and optimized to run as fast as possible to keep up with the very high rates of data capture from RFeye receivers. Rapid visual refresh rates enable users to derive maximum intelligence from the data.

Sweeps and time captures

RFeye software provides a familiar and simple spectrum analyzer interface for each connected RFeye Node, with real-time frequency and time domain spectra and constellation diagrams, 2D or 3D waterfall displays. Each Node can be output to individual displays, or displays can be combined and overlaid for more powerful analysis options with selectable data processing modules. Individual elements of a more complex mission can be controlled and configured per Node. For example, after obtaining a TDOA geolocation result using a GPS synchronised RFeye network, an individual Node can be selected based on proximity to the signal for targeted time captures and further detailed analysis.

Masks, triggers and alarms

The software can be configured to issue alarms via the local system, to log files, SMS and email from user-defined triggers and spectrum masks. Simple mask-break scenarios can be useful for triggering alarms when any signal exceeds an expected background spectrum of known signals, or more advanced modules allow notifications on events such as detection of certain modulation types and channel identification.


Resolve complex interference in real time.

Many different signal types are potential sources of interference, indicators of illegal activity or unauthorised spectrum use.

Direction finding and individual geolocation techniques are each effective for only a limited range of target signal types, which varies according to many factors including signal bandwidth, modulation, power, background noise, pulse duration and receiver speed.

The most reliable and cost-effective method to ensure detection and successful localization of the maximum range of target signal types is to combine each technique in a single real-time overlay. The RFeye® supports multiple DF and geolocation techniques including Angle of Arrival (AOA), Time Difference of Arrival (TDOA) and Power on Arrival (POA).

Signal Classification

Using machine learning techniques and an extensive training data set, CRFS has created a highly accurate signal classifier.

The RFeye® Signal Classification module is able to identify a comprehensive range of modulation types, both analog and digital, covering military and civilian standards. The module identifies the modulation technique of a signal of interest and returns it in string format. This gives you center frequency along with modulation type (“QPSK” or “QAM,” for example), the number of modulation levels, modulation index and baud rate. All of this helps to identify the type of transmission detected and can allow operators to diagnose causes of interference and identify possible threats.

The RFeye Signal Classification module has been developed using the latest Machine Learning techniques and mathematical tools to train neural networks and CRFS’s very extensive training data sets of signals. Machine learning techniques are ideal for optimizing signal classification performance and allow for very fast accurate signal classification while minimizing false alarms and permit easy updating of signal classifier databases with new signal types.

How does it work?

During the training process, the performance of the neural net can be monitored using a confusion matrix as shown below. The input data for training neural nets is a large database of signal types collected from real-world RF environments using CRFS-distributed RF sensors located all over the world. The more signal types, with real world distortions such as multipath, the more effectively the neural net can be trained to perform in actual field deployments.

Confusion matrix for signal recognition

The CRFS training database uses “tagged” signals with known classifications to train the neural net. The training process adjusts individual neurons in the net so that they can identify the known signals correctly, i.e., the classifier’s calculation and the “tag” match.

To test the neural network, a separate set of known signals not used for the training process is input to the classifier. The confusion matrix shows the known input signal type against the classifier’s calculation for every test and increments the appropriate element of the matrix with the answer against the test input. In other words, a 100% correct classifier would produce a confusion matrix with non-zero elements only along the leading diagonal. Generally, test scores of >95% accuracy can be achieved. These test scores improve with more varied and deeper training data sets. CRFS is actively building massive tagged-signal training databases for this purpose.

Typical signal classifier neural network

The input layer of a neural net has a series of weightings from features extracted from signal IQ data, e.g., 20 feature weightings and 20 input neurons. The output layer has a neuron for each signal type to be classified, e.g., 30 signal types and 30 output neurons. The neural net selects the output signal type to reflect the most probable signal given the input features.

Signal Verification

RFeye® software includes an optional Signal Verification module that is used to test and verify that signals in channels (e.g., TETRA, DAB, GSM) are of the type authorized for those frequency bands. The software displays alerts for any transmissions that are not of the allowed or expected type within the channels.

Results are displayed on a color-coded spectrum (see above). Not only does this allow detection of incorrect signal types, but also less obvious infringements such as incorrect guard-band ratios and symbol durations.

Applications include regulatory and enforcement as well as verifying that a user’s own transmitter equipment is functioning correctly.

Record and playback

The software allows data to be recorded and played back via a simple interface. Recording can be manual using the “record” button, and all data processes that are running in the software at the time will be recorded. Alternatively, recording can be set to trigger at a mask breakage, in which case all data relating to the mask breakage will be recorded using predetermined parameters.

Spectrum mapping

Large sets of spectrum data can be automatically aggregated, processed and overlaid onto a map to provide a clear and easily-inspectable visual representation of spectrum usage. This is particularly useful for regulators, military users and event planners wishing to consider RF congestion risks. The spectrum map is also used by regulators to observe spectrum usage and coverage over time, allowing more informed decisions on licensing.

The software is able to display and analyze spectral data in a number of different ways, including synchronized map-based displays, spectrum plots and spectrograms, occupancy plots and time evolutions. Data can be selected by any combination of RFeye Node/network, location, time window or frequency range, and resolution can be displayed from the national level to an individual street location. Data can be displayed and analyzed from both mobile and fixed-monitoring operations. Many different reports can be produced and tailored to specific requirements.

The data handling and processing efficiency of the mapping tool allows the operator to quickly interrogate the entire database to understand and resolve potentially complex real-world spectrum issues. A series of graphical reporting tools are linked and updated simultaneously with the geospatial representation of measured spectrum on the map overlay. The available visual representations on the map overlays include mean signal, peak signal and band utilization. Reporting options include spectrogram charts for temporal analysis, spectrum charts for summarizing signal power by frequency, and spectrum-use reports to step through the selected data set at user-defined resolutions to understand total spectrum utilization across an area.

Spectrum database

RFeye® software includes an integrated package of tools for data logging, data transfer, database storage and filtering, and web display of requested results. These tools have been designed to provide a seamless user experience through a secure and streamlined web-based application interface.

Once logged, data sets are transferred from the RFeye Node into the database. This can be done in a number of ways to suit requirements and will normally involve either UDP or TCP data transports. The database is capable of storing several different types of data, including text, spectra, occupancy, time, cell survey, temperature and voltage, as well as information about the network and individual campaigns. It uses a single comprehensive library of scripts able to deal with data provided by any of the possible data transfer mechanisms.

The data from the database are accessed via a configurable web portal. The portal allows users to query the data and graph the results, as well as to create individual campaigns to run on the distributed Nodes. It provides secure logins and varying levels of access based on user privilege.


Users can define and run multiple simultaneous spectrum-monitoring campaigns. Campaigns can be assigned to the entire RFeye network, sub-groups and regional networks, or individual sites as required. In addition to background spectrum monitoring, campaigns are defined for specific missions such as to monitor ISM band usage, TETRA interference, GSM and UMTS coverage, suspected GPS and other jammers. Campaigns can be configured in response to events such as mask breakages and conditional expressions, allowing targeting of spectral events of interest.

Occupancy data aggregation

With rising RF spectrum usage, regulatory authorities need to be increasingly aware of congestion risks. Occupancy measurements allow assessment of both existing congestion issues as well as pre-empting possible future issues. With the RFeye software, occupancy measurement and inspection can be done on an ad hoc basis, or by using a more formal tool that issues regular reports and alerts on the status of particular frequency bands of interest. This is useful not only to spectrum regulators, but also for military users wishing to identify suitably non-congested frequency bands for an operation, or for any spectrum user wishing to ensure the integrity of their transmissions. Real-time occupancy measurements are particularly valuable at events such as sporting competitions and concerts where high numbers of attendees can place abnormal strain on spectrum.

Users can run queries by individual Node or aggregated groups for occupancy by time or frequency during any selectable period of time. The Nodes take measurements at the requested rate based on power measured above a threshold, in accordance with ITU recommendation SM.1880 for occupancy.

Sweep and time capture data

The interface allows the user to zoom from broad-range frequency occupancy data (aggregated from the entire RFeye network) to tracking of occupancy by time for specified frequencies of interest at particular Node locations. This enables quick drill-down from spectrum events spotted in top-level overview reports to a detailed localized timeline of spectrum activity surrounding the signal of interest. This information can be combined with other features such as spectrum licensee status to provide further layers of context for decision-making.

License database

Spectrum licence information can be uploaded (as a pub7 file for example) to the licence database for easy management. Although this information is fixed, only changing as new licences are granted, unlimited modifications can be made by the user even to the point of creating an entirely hypothetical licensing scheme. This data can then be integrated with other RFeye software functionality, for example, by overlaying the data onto spectra.

Propagation Analysis

The Propagation Analysis module is a software plug-in that can be used to accurately model wide-area spectrum monitoring capabilities at real-world locations.

The Propagation Analysis module offers immensely powerful RF simulation, planning and analysis tools for both natural topographical and man-made structural features.

The terrain data is first analysed for initial placement of receiver stations. This analysis allows the user to investigate the impingement on the first Fresnel zone between the receiver and potential target location. The analysis tools then use the built-in propagation models to investigate receiver and geolocation coverage. Most geolocation techniques require simultaneous data from one or more receivers, so a coverage analysis looks at how many receiver coverage areas can be seen at the same time. The receiver stations can then be best positioned to optimize the geolocation techniques being used.

The propagation of RF signals can be modeled to varying degrees of complexity. In the most basic form, the Free Space model can be used; this simply relies on the Friis Transmission Equation, allowing simulation of the decrease in received power for increasing frequency and distance from the transmitter. Complexity and real-world correspondence is cumulatively built up with Earth Curvature, Line of Sight and Fresnel models, allowing the inclusion of horizon effects, obstacle shadowing, and obstacle diffraction and reflection effects respectively. This propagation modeling ensures the accuracy of geolocation and monitoring simulations as well as allowing propagation-analysis coverage maps to be generated.

Spectrum manager

Receiver Nodes can be set to automatically upload spectrum measurements to a database. This allows remote viewing of Node data over IP as well as querying, filtering and graphing of the measurements of interest. Whether you’re organizing Nodes into user-defined groups or searching occupancy graphs by time and date, RFeye® software makes large networks, and the resulting data, easy to manage.

Other database functions for big spectrum data include management and filtering of historical spectrum sweeps for overlay onto spectrum maps and management of licenses with the licence database.

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