The Evolution of RF Signal-Observation Tools

The Evolution of RF Signal-Observation Tools

This article appeared in Microwaves and RF and Electronic Design and has been published here with permission.

Tools used to visualize RF signals have evolved over time from the spectrum analyzer to today’s RF recorders. However, each era’s tools have had limitations. This article shows how the modern approach builds on the best aspects of what’s come before.

What you’ll learn:

  • RF signal observation has evolved from yesteryear’s spectrum analyzer to today’s RF recorder.
  • Swept spectrum analyzers, FFT analyzers, and real-time signal analyzers all had limitations.
  • Today’s RF recorders build upon the foundation of earlier generations of instruments.

RF engineers have always been obsessed with pursuing new and better ways to observe and analyze RF signals. In the earliest days of RF engineering, pioneers like Nikola Tesla struggled to simply generate wireless signals, much less analyze them.

We can only imagine the daily struggle involved in attempting RF engineering without any instrumentation. It’s quite a leap from the crude laboratory of Tesla to the sophisticated analyzer we take for granted today. But today’s instrumentation is actually the result of many decades of incremental improvements. Here’s a brief overview of the many steps in the evolution of tools for RF-signal observation.

The Swept-Tuned Spectrum Analyzer

Undoubtedly, the most important breakthrough in RF instrumentation occurred in the late 1950s and 1960s with the emergence of swept-tuned spectrum analyzers. At last, here was a means of viewing signals in the frequency domain. It knocked the oscilloscope off its pedestal as the most important instrument in the RF engineer’s toolbox in much the same way as the Ford Model-T replaced the horse and buggy.

The repercussions of this class of instrumentation can hardly be understated as it played a key role in the exponential growth of the biggest test and measurement companies in the world. From this point, the race was on to incrementally improve the spectrum analyzer and overcome its limitations. 

Limitations of the Swept-Tuned Spectrum Analyzer

The most fundamental limitation of the swept-tuned spectrum analyzer is its inability to cleanly characterize a time-variant signal. Because the instrument slowly sweeps a range of frequencies, the signal displayed on the screen is a composite of many acquisitions taken across the sweep time. The result: a screen display of a signal that never actually existed in the real world.

While this limitation may have been an acceptable compromise for relatively stable AM and FM signals, it was completely untenable for short, bursted signals like radar. In the ensuing years, various attempts were taken to overcome this limitation using more and more elaborate triggering schemes, correction factors, and zero-span modes. Ultimately, this struggle sowed the seeds for the next big breakthrough in spectrum analysis.

Emergence of the FFT Analyzer

Because signal analysis was a particularly pressing issue for defense applications, industry and government directed substantial resources toward developing a digital fast Fourier transform (FFT) spectrum analyzer. This new type of analyzer promised to capture the entirety of the wideband signal in one acquisition instead of creating a composite of many acquisitions.

Two technologies had to emerge to enable the FFT analyzer to become viable. The first was high-speed analog-to-digital converters (ADCs). The second was digital processors that could quickly compute an FFT. The efforts were successful and by the late 1980s, very capable FFT analyzers were found on the benches of defense laboratories across the globe. By the mid-1990s, the emergence of digital cell phones accelerated the commercial adoption of FFT analyzers.

Limitations of the FFT Analyzer

The FFT analyzer was revolutionary for many applications, but it still had significant dynamic-range limitations. Even more importantly, it had substantial acquisition dead time as part of its measurement cycle. Ultimately, this resulted in limited fidelity in the time domain.

While the instrument was busy computing the FFT from the prior acquisition, it was blind to all other incoming signals. This became the catalyst for the next incremental improvement in spectrum-analysis instrumentation: the real-time spectrum analyzer (RTSA).

Real-Time Spectrum Analyzer

In the late 1990s, very fast DSP silicon emerged that was perfectly tuned to execute efficient FFT computations. This development made possible the creation of the RTSA.

At its core, the RTSA is an FFT analyzer with rapid FFT bolted onto the back end. The FFT computations occur so quickly that the RTSA provides the user with the illusion of continuous acquisition with no dead time. With this architecture, the probability of missing signals was dramatically reduced. This added capability is particularly important in spectrum monitoring and signal-intelligence (SIGINT) applications.

Limitations of the RTSA

Unfortunately, the real-time spectrum analyzer (RTSA) still presents the RF spectrum to the user as a series of separate acquisitions. The RTSA must break up the signal into multiple, discrete blocks to compute an FFT and present the information to the user.

However, even more importantly, the RTSA doesn’t create a permanent record. Without a permanent record, signals are fleeting—they occur, they’re displayed, and they disappear without a trace. The RTSA doesn’t fundamentally change the operator’s workflow in a way that would allow for multiple, transient signals to be frozen in time, replayed, and analyzed later.

Enter the RF Recorder

The RF recorder is the latest iteration in the century-long quest to improve spectrum analysis. It builds upon all previous generations of spectrum analyzers with the added capability of storing a permanent record of raw RF signal data.

Unlike the RTSA, most RF recorders don’t need to break an incoming RF signal into discrete chunks for further FFT processing. Instead, these instruments natively capture time-series data. A truly continuous, gap-free stream of RF signal data is preserved as a permanent record.

Of course, most human operators will not gain much insight by viewing raw times-series IQ data on a screen. A well-designed RF recorder, such as Spectra Lab’s Spectrum Defender, will record time-series data but still allow the operator to view signals in a conventional spectrum-analyzer-style display. Under the hood, these RF recorders are retrieving time-series data from disk and computing a “just-in-time” FFT to create a user-friendly, frequency-domain display.

Importantly, this instrument architecture enables the user to change the FFT length (and related resolution bandwidth) to any desired value, at any point in the future, without fundamentally altering the underlying record of signal data. With a time-series RF recorder, there’s no need to worry about the FFT length or resolution bandwidth used when the signal was originally observed or recorded in the field. This is a neat trick that the RTSA is hard-pressed to duplicate.

The permanent record provided by an RF recorder allows us to capture a true, continuous view of the electromagnetic environment with no acquisition dead time, and no advance knowledge of the optimum FFT length. Engineers can retrieve and interrogate any portion of the RF spectra on demand in the time domain, frequency domain, or joint time-frequency domain. The very latest RF recorders even allow engineers to capture spatial-domain information with multiple phase-coherent channels.

One hundred years ago, that wasn’t something Nikola Tesla could have ever imagined.

This article appeared in Microwaves and RF and Electronic Design and has been published here with permission.

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