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RTSA: How “Real” is Real Enough?

Blog Post created by benz on Oct 14, 2016

Originally posted May 18, 2016

 

Improving your chances of finding the signals you want

 

Real-time spectrum analyzers (RTSAs) are very useful tools when you’re working with time-varying or agile signals and dynamic signal environments. That’s true of lots of RF engineering tasks these days.

A good way to define real time is that every digital sample of the signal is used in calculating spectrum results. The practical implication is that you don’t miss any signals or behavior, no matter how brief or infrequent. In other words, the probability of intercept (POI) is 100 percent or nearly so.

Discussions of real-time analysis and the tracking of elusive signals are often all-or-nothing, implying that RTSAs are the only effective way to find and measure elusive signals. In many cases, however, the problems we face aren’t so clear-cut. Duty cycles may be low, or the signal behavior in question very infrequent and inconsistent, but the phenomenon to be measured still occurs perhaps once per second or more often. You need a POI much greater than the fraction of a percent that’s typical of wideband swept spectrum measurements, but you may not need the full 100 percent. In this post I’d like to talk about a couple of alternatives that will make use of tools that may already be on your bench.

A good example is the infamous 2.4 GHz ISM band, home to WLANs, Bluetooth, cordless phones, barbecue thermometers, microwave ovens, and any odd thing you IoT engineers may dream up. Using the 89600 VSA software, I made two measurements of this 100 MHz band, changing only the number of frequency points calculated. That setting affected the RBW and time-record length, as you can see here.

Two spectrum measurements of the 2.4 GHz ISM band, made with the 89600 VSA software. The upper trace is the default 800-point result, while the lower trace represents 102,400 points. This represents a 128x longer time record, long enough to include a Bluetooth hop in addition to the wider WLAN burst.

Two spectrum measurements of the 2.4 GHz ISM band, made with the 89600 VSA software. The upper trace is the default 800-point result, while the lower trace represents 102,400 points. This represents a 128x longer time record, long enough to include a Bluetooth hop in addition to the wider WLAN burst.

The 102,400-point measurement has several advantages for a measurement such as this. First, it truly is a gap-free measurement: For the duration of the longer time record, it is a real-time measurement. Next, it contains more information and is much more likely to catch signals with a low duty cycle. It has a narrower RBW, making it easier to separate signals in the band, and revealing more of the structure of each signal. When viewed in the time domain, it can show much more of the pulse and burst signal behaviors in the band.

Another advantage of the larger/longer 100K-point measurement is not as obvious. The total calculation and display time does not increase nearly as rapidly as the number of points, making the larger FFT more efficient and increasing the POI. In my specific example, the overall compute and display speed is almost 20 times faster per point, with a corresponding increase in POI. It’s that much more likely that elusive signals will be found—or noticed—even without an RTSA.

For the RF engineer, however, this flood of results can be hard to use effectively. It’s difficult to relate the many successive traces to signal behavior or band activity as they fly by. The key to a solution is to add another dimension to the display, typically representing when or how often amplitude and frequency values occurred. Here are two displays of a 40 MHz portion of that ISM band.

Many measurement results can be combined in a single trace to help understand the behavior of a signal or the activity in a frequency band. The top trace shows how often specific amplitude and frequency values occurred over many measurements. The bottom trace uses color to show how recently the values occurred, producing a persistence display.

Many measurement results can be combined in a single trace to help understand the behavior of a signal or the activity in a frequency band. The top trace shows how often specific amplitude and frequency values occurred over many measurements. The bottom trace uses color to show how recently the values occurred, producing a persistence display.

These traces make it easier to intuitively interpret dynamic behavior over time and understand the frequency vs. recency of that behavior. Thus, the combination of large FFT size and cumulative color displays may provide the dramatic improvement in POI that you need to find a problem. For precise measurements of elusive signals and dynamic behavior, the 89600 VSA offers other features, including time capture/playback (another variation on real-time measurements over a finite period) and spectrograms created from captured signals.

As professional problem solvers, we can figure out when a finite-duration, gap-free measurement is sufficient and when the continuous capability of an RTSA is the turbo-charged tool we need. In either case, it’s all about harnessing the right amounts of processing power and display capability for the task at hand.

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