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Real-time Analyzers: Understanding the Choices in Spectrograms

Blog Post created by benz on Sep 20, 2016

Originally posted Oct 11, 2013

 

Which real-time view is best for you?

By now, you’ve probably heard of real-time spectrum analyzers. These blazing-fast instruments calculate hundreds of thousands of spectra per second, ensuring that all samples are processed and nothing is missed—even when analyzing wide frequency spans and the fast sample rates they require.

As you might imagine, this kind of speed presents a display challenge: How do you represent nearly 300,000 spectral results per second in a way that’s useful to an RF engineer? After all, our goal is notmore measurements but better measurements.

For compatibility with human visual systems, signal analyzers update their displays about 30 times per second. With 300,000 spectra per second, each display update must somehow represent approximately 10,000 spectrum calculations. Aside from simple peak or average calculations, the two most common representations of this “big data” are histogram or density displays (the subject of a future post) and spectrograms. Density displays summarize the frequency of occurrence of specific amplitude/frequency combinations, and this is a good way to reveal infrequent signals or those with very low duty cycles.

In contrast (pun intended), spectrograms represent large amounts of spectral data with a focus on timing. As with normal spectrum displays, the X-axis is a frequency axis; however, the Y-axis changes from amplitude to time, and amplitude is represented with color. As a result, the display can show at a glance how the power spectrum changes over time, and a spectrogram of real-time data can represent everything that happens over a wide span and a selectable time interval. Two examples of over-the-air spectrograms from the 2.4 GHz ISM band are shown in the figure below.

This shows two real-time spectrograms of the 100-MHz ISM band centered at 2.45 GHz. WLAN, Bluetooth and cordless telephone signals are shown. The frequency acquisition times set the time represented by each slice or pixel row and thus the time covered by the full spectrogram.

This shows two real-time spectrograms of the 100-MHz ISM band centered at 2.45 GHz. WLAN, Bluetooth and cordless telephone signals are shown. The frequency acquisition times set the time represented by each slice or pixel row and thus the time covered by the full spectrogram.

These spectrograms show the same signals and use the same measurement settings except for one: frequency acquisition time. In the top view, each display update (30/s) adds a single pixel row or slice to the spectrogram. The pixel row summarizes about 10,000 spectrum calculations using a peak-hold algorithm that is the default “display detector” type. Other available detectors include average, sample and negative peak.

Because this spectrogram is about 400 rows high, it represents a measurement interval of about 12 seconds and reveals a lot of information: apparently continuous WLAN traffic on 18 MHz channels, Bluetooth frequency-hop patterns (top), bursts from a cordless phone (center) and some WLAN channel scanning or switching (center left). The 12-second interval is long enough to show general signal behavior and catch infrequent events such as cordless phone activity and WLAN scanning and switching. However, the available time resolution is 30 ms and this is too coarse to show how the ISM band is shared by WLAN bursts and the much shorter Bluetooth transmissions.

The bottom spectrogram provides a dramatic increase in time resolution. The level of detail helps explain how a single band can support so many different users if it implements spread-spectrum techniques such as frequency hopping and pulsed or framed OFDM. The frequency acquisition time has been reduced to 1 ms and thus the spectrogram covers just 0.4 seconds. Because the analyzer’s display update rate for the spectrum is unchanged, each pixel row summarizes about 300 spectra, and 30 pixel rows must be added for each update. As a result, the display scrolls by more rapidly.

Although both spectrograms are accurate measurements of activity in the ISM band, they reveal different phenomena and do so with different tradeoffs. For example, deep, scrollable trace buffers and a slice marker (the white horizontal line in each spectrogram) allow the user to review larger blocks of spectrogram data and display individual spectrum results for each pixel row. No matter what frequency acquisition time is selected, the real-time spectrogram can cover the entire band and ensure that no signal is missed.

If needed, much greater time resolution is available using the same signal analyzer platform with a different type of real-time analysis: time capture and playback. That technique, along with its benefits and tradeoffs, will be the subject of another post.

For more information on real-time analysis and the Agilent PXA and MXA X-Series signal analyzers, see this application note.

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