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One Solution to Complexity: Focus on the Most Common Measurement Errors

Blog Post created by benz on Sep 10, 2017

  A pre-filter to manage an excess of information

In the first two decades of the modern spectrum analyzer—say from the 1960s to the 1980s—it was arguably possible for an RF engineer to know almost everything about making spectrum measurements. One reason: the signals and the analyzers were relatively simple.

Signals were generally assumed to be CW or pulsed CW. Noise and signal-to-noise measurements were straightforward adjustments from spectrum results. Pulsed signals were similarly measured by interpreting conventional spectrum results.

RF spectrum analyzers used a superheterodyne architecture with fundamental mixing, and microwave analyzers used harmonic mixing to cover the higher bands. A semiautomatic technique was adequate to identify images or other false responses, if preselection was not available.

Things have changed immensely in the past 25 or 30 years: the transition from analog to digital modulation; the development of advanced radar and EW systems; and the overcrowding of the airwaves we all share. In lockstep fashion, the corresponding measurement standards have grown in size and complexity.

All these advances have driven a process of mutual bootstrapping, one that has transformed spectrum analyzers into signal analyzers. Built around a wealth of digital technologies, today’s analyzers offer options for modulation analysis, vector signal analysis, and real-time spectrum analysis.

Thus, software has become a vital part of these signal analyzer solutions, frequently in the form of measurement applications. Some, such as PowerSuite, are broad and general purpose. Others are highly specific, designed to make complex sets of measurements in compliance with a particular standard such as LTE or 802.11ac.

These synergistic tools—hardware and software—are now essential for RF engineering. However, if success depended only on starting an app and pressing the right buttons, there would be no need for clever and dedicated engineers. In the real world, successful design and troubleshooting require myriad measurements and setups, and a deep understanding of the results.

If we can no longer know everything about our signals and tools, how do we ensure that we know the right things? I can make no guarantees, but I can offer a few suggestions to help you stay current while keeping the time and effort reasonable.

Discussion forums and blogs: Those that focus on test equipment, such as the one Keysight hosts, are a way to explore common issues and interact with other users, including experts from the manufacturers. Test and measurement blogs are often a companion to the forums, providing news and commentary in specific areas.

Webcasts, both live and recorded: Because I’m rarely in complete control of my schedule, I especially appreciate recorded webcasts. They’re a source of the specific information I need, just when I need it, even late at night or on a weekend. Search engines and webcast collection pages can help you find the one you need.

Articles on common problems and errors: A surprisingly useful type of article is an expert explanation of the most common measurement errors or problems in a given area. At their best, these articles can be a pre-filter that distills unmanageable amounts of measurement knowledge into actionable advice. Such articles also tend to be relevant across time and evolving technology, as this one from Keysight’s Bob Nelson demonstrates. For example, he explains how the log of an average is not the same as the average of a log, and how display detectors yield different answers from the same measurement data.

A single measurement data set is processed by three display detectors to produce three measurement traces, signified by different colors. The detectors are peak, minimum, and "normal."

Three display detectors produce three different measurement traces from the same data set. The “correct” answer depends on the purpose of your measurement.

Serendipity: I can’t count the number of times I’ve learned something important and useful just by chance. The source may have been an offhand comment, an article stumbled upon, a random encounter with another engineer, or the intersection of a search engine and my inherent curiosity. While I can’t rely on these happy accidents, I must confess to feeling slightly uncomfortable with how often they occur.

I realize that for most of you, measurements are a means to an end, enabling your real job: doing the engineering that drives the next waves of ever-advancing technology. It is often an uphill trek that leaves precious little time for simply keeping up. If you have any additional tips for success, please chime in with a comment.

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