Wideband systems for RF signal capture and analysis
There are many applications that require the capture and analysis of radio signals. Government bodies may need to review signals to check compliance with the appropriate regulations, or to assess any problems with interference. For example, in the UK, Ofcom acts as the independent regulator for the communications industry, and in Germany the Bundesnetzagentur ensures compliance with the country’s telecommunications act.
Another requirement is for COMINT (communications intelligence) and ELINT (electronic intelligence). This kind of work deals with intercepting and analysing communications, typically for surveillance or information-gathering.
The signals captured can include a wide range of RF frequencies, whether they are from satellites or other sources. Depending on the application, a user may want to record the signals, analyse them in real time, or store them for offline processing. There is also a need to archive the captured signals for later reference.
Typical radio monitoring applications require a flexible access scheme where all intercepted signals are buffered, while operators or automatic classification and analysis tools browse through the available content.
Wider bandwidths needed
While this kind of monitoring and analysis is a long-established application, there is a recent trend towards continuous surveillance of all signals across wider bandwidths. Instead of selectively monitoring individual transmissions, organisations want to run automatic signal collection and analysis, all the time.
The objective of this continuous monitoring is to ensure that no relevant transmissions are missed. This puts additional demands on the equipment used, both in terms of the wider bandwidths targeted, and in the sheer quantity of data generated.
Another driver towards wider bandwidths is cost reduction by minimising the number of RF receivers required. Traditionally, organisations might use many narrowband receivers to monitor a frequency band – possibly as many as several hundred, if needed. If a single device could capture signals across a much wider bandwidth, this would allow fewer receivers to be used, thus saving money.
Finally, wider bandwidths are increasingly required simply due to the wide bandwidth of signals to be monitored. For example, global navigation satellite systems (GNSS), such as GPS and the European Galileo system, typically have signals across a wide bandwidth. GNSS satellites transmit navigation signals in the L band, which covers the 1 to 2 GHz portion of the radio spectrum – for instance, the GPS L1 band uses a centre frequency of 1575.42 MHz. The bandwidth of the signal itself can be measured in tens of MHz, which can cause problems for narrowband receivers – the best way to handle the full bandwidth is to use a wider band receiver.
Next: What’s the solution?
Hardware and software solutions
To meet these needs for continuous monitoring and wide bandwidths, manufacturers are developing hardware and software solutions that provide the performance required. Let’s look at one example: the R4000 from IZT, with its associated Signal Suite software.
The R4000 is a digital receiver and signal collection system, and is designed to meet customer demands for dynamic range even in high-bandwidth applications. It supports multiple simultaneous users on multiple channels.
As discussed earlier, bandwidth is a key factor in many applications. The R4000 provides an instantaneous bandwidth of 120 MHz, meaning it can handle GNSS data or other sources of wideband signals. This means that it can be used to replace multiple narrowband receivers, without compromising quality.
It is worth pointing out that wideband receivers such as the R4000 use software-defined radio (SDR) capabilities to implement parts of the system. As a technology, SDR is capable of achieving the highest levels of RF quality, as long as it is combined with traditional high performance tuners before the analogue to digital conversion.
Next: Selective recording
Selective recording
Of course, with such a wide bandwidth, there will be huge amounts of data generated. Any practical solution needs to be able to store and analyse this data, but one way to minimise the problem is to be selective in which segments of the signal are examined.
With the R4000, all intercepted signals are stored in the first instance. Then, multiple operators or automatic classification and analysis tools can be used to browse through individual streams or multiple streams in parallel, no matter whether they were recorded in the past or are real time.
This means that users can specify criteria to determine the signals of interest. For example, they could only look at signals where the incoming power exceeding a certain threshold. The determining factors can be independent of threshold, such as only taking eight fixed sub-bands within the 120 MHz bandwidth, and continuously monitoring these smaller frequency regions. In fact, the R4000 can extract up to 32 sub-bands, which may overlap.
Automatic selection needs to happen quickly, with minimum latency. To achieve this, after digitisation, the R4000’s DSP section calculates fast, high-resolution power spectra (PSD) with configurable parameters and three different detectors (minimum, RMS and maximum) in parallel. This PSD data gives an overview of the activities in the frequency band, and can serve as a trigger source for selective capture.
Figure 1: Energy Detection
Next: Arbitrary extraction
In the past, dynamically shifting the centre frequency of the region being captured would tend to cause data corruption, or for the signal to be dropped. The R4000 overcomes these problems, and allows arbitrary sections of the spectrum to be extracted, and the region of interest to be varied in real time without affecting signal integrity.
The R4000 digitizes signals up to 140 MHz directly without additional frequency conversion, helping to improve dynamic range. For higher-frequency applications, the input frequency range can be extended to 3 GHz or 18 GHz, using the VUHF or SHF front ends. The R4000 includes highly-selective configurable signal pre-selectors to avoid signal overload problems, high-quality RF front-ends, and broadband digitizers.
Figure 2: IZT R4000 overview
Software integration and storage
Capturing the signal is just the start of the process – how can it be analysed and stored? In today’s systems, there is close integration between software and hardware to provide the most useful tools. For some applications, the complex post-processing algorithms required are sometimes too slow to work in real time, so it is essential to store signals and process them offline.
Next: Look and feel
The R4000 storage system separates signal capture from post processing and analysis, providing minutes to days of buffering capacity, if required. The storage hardware used depends on the use case, with varying sizes possible of hard drives or solid-state storage.
While new data from the sensors is being recorded, multiple users or post-processing modules can simultaneously access historic data in the storage system as well as live streams. The transition from live to recorded is completely seamless from the users’ point of view.
To handle the vast amount of data generated, an effective graphical user interface is needed. For example, the R4000’s software provides a customisable layout that can be switched from a basic overview to a fully detailed view. Customisable templates restrict the interface, helping users to focus on specific tasks.
A Software Development Kit (SDK) and open data formats ensure easy interaction with third party software and system integration. This feature is commonly used to analyse signals with MATLAB.
Figure 3: Viewing captured data in Signal Suite software
Next: Distributed systems
Distributed systems
The R4000 backend system also allows distributed operation over different locations, supporting multiple sensors and multiple users. This means that it is possible to install the sensor at remote locations while data processing and visualisation happens at a central command post – even with unreliable or slow network connections.
All signals are recorded and cached at the remote location. Users or software modules request a preview of areas of interest. A variety of compression algorithms reduce the amount of data that needs to be transferred to the central command location, and users can configure the trade off between quality and speed.
Should the network go down, access to the sensor will be temporarily unavailable, but the remote storage system will continue recording and store all signals for later analysis.
If the full content of a signal is needed, it can be compressed with configurable quality and transferred to the central location, possibly during times of low network use.
Conclusion
Many organisations have a need to monitor, analyse and store radio signals. With bandwidths growing, and the number of devices to be monitored also increasing, this creates a requirement for equipment that can capture wideband signals, and can deal with the large amount of data created.
With suitable integration of hardware and software, it’s now possible to meet this challenge, and to provide a user-friendly, cost-effective solution that meets the needs of government regulators and other bodies.
About the author:
Rainer Perthold is CEO of IZT Labs GmbH, a spin-off of Fraunhofer Institute for Integrated Circuits (IIS) and an expert company for RF and microwave technology.
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