benz

An old spectrum analyzer nemesis, and one way to tame it

Blog Post created by benz on Sep 16, 2016

Originally posted Feb 20, 2014

 

There’s no shame in being average—if you can get there quickly

In RF testing, noise and the measurement variance it causes are sometimes the biggest things standing between you and better measurements. The combined effect can limit amplitude accuracy and effective resolution, and the various approaches to minimizing the effect can severely hinder measurement speed.

In a previous post, I complained about how noisy the universe is—though I understand if you have no sympathy for me!—and promised to discuss efficient averaging techniques. One of the best is a display feature called the average detector.

To explain the average detector and its advantages, here is the block diagram from my recent post Detector decisions: see it your way.

This partial, simplified block diagram of a spectrum analyzer shows the two detectors and their locations in the signal path. The video detector converts the IF signal into a magnitude value and has no user controls. The display detector is controlled by the user and determines how varying magnitude values are converted to measurement points.

This partial, simplified block diagram of a spectrum analyzer shows the two detectors and their locations in the signal path. The video detector converts the IF signal into a magnitude value and has no user controls. The display detector is controlled by the user and determines how varying magnitude values are converted to measurement points.

A traditional way to reduce measurement variance due to noise is the video bandwidth (VBW) filter. It’s simply a lowpass filter acting on the detected amplitude of the signal in the analyzer’s IF section. The detector output is called a video signal and the VBW filter thus smoothes the trace and performs an averaging function. Very simple and clever, and it has some advantages for measuring CW signals near noise. Unfortunately, these benefits often affect measurement speed, and I’ll discuss the tradeoffs in a future post.

Note, however, that the VBW filter is usually averaging a log-scaled signal. It is performing an average of the log of the signal and, as explained previously, The Average of the Log is Not the Log of the Average unless the signal in question is CW. These days it seems like only a minority of the signals we measure are CW, and we don’t want the amplitude statistics of the signal to foul up our average or accuracy—so what are we to do?

In current-generation spectrum/signal analyzers, the answer is the average detector. These analyzers use digital IF/video detectors that respond to linear signal power (watts, not dBm) and therefore an average detector can calculate the log of the average power. The figure below illustrates the process of averaging all the linear power values between buckets and displaying the result for one display point.

The function of the average detector is enlarged and shown over an interval of slightly more than one display point. The average detector collects many measurements of IF magnitude to calculate one value that will be displayed at each bucket boundary.

The function of the average detector is enlarged and shown over an interval of slightly more than one display point. The average detector collects many measurements of IF magnitude to calculate one value that will be displayed at each bucket boundary.

The average detector has several important advantages in accuracy and speed. Calculating an average of linear power values and expressing the result in log or dB form produces a result that is accurate independent of the signal statistics. Averaging values between display buckets allows the high sampling rate of the IF detector to be used to best advantage, with no samples thrown out. This maximizes variance reduction in the shortest time.

Finally, using the average detector allows the amount of averaging—and therefore variance reduction—to be easily increased simply by slowing the sweep speed. This is generally a more time-efficient method than trace averaging, in which many successive sweeps are needed to perform a good average (in part because many between-bucket samples may be thrown out).

By the way, the use of an average detector on a power scale is often referred to as RMS averaging or even an “RMS detector.” This usage is a bit confusing because there is no RMS detector per se; however, it indicates that the result is an accurate measurement of the RMS power of a signal, independent of its amplitude dynamics.

Of course, the average detector is not always the best choice and there is more to say in this area, especially in terms of averaging scales and the averaging processes in spectra/signals. Stay tuned.

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