Originally posted Mar 1, 2013
One core concept to explain real-time measurements
“Real-time” in signal analysis is an important concept but it means different things to different engineers, and the common conflation with “real-time analyzers” can make explanations more complex than they need to be. Here’s a starting point for a productive understanding of the whole thing:
In a modern RF analyzer with a digitally sampled IF section real-time means all signal samples are used in calculating measurement results.
Where results are calculated from a time record (block of samples) “T” and the time for calculations and display updates is “Calc” we can explain the situation with this diagram:
Real time analysis means that all signal samples are used to calculate results, or that the calculations are gap-free relative to the stream of signal samples.
If the analyzer frequency span (and therefore its sample rate) is increased as shown in the middle of the figure, the time length of the time record T is shortened proportionally. At some wider frequency span the time record fills just as fast as the Calc time and the analyzer has reached its real-time bandwidth or RTBW. Measurements wider than this frequency span will no longer be real-time.
However even when all samples are included in a calculation for this type of real-time analysis, some samples may be effectively lost due to a process called “windowing” the time record. That process, its benefits, and the use of overlap processing to counter its effects will be discussed in a future post.
One other type of real-time analysis is important here: Time capture followed by post-processing. In this alternate approach the samples are streamed to fast memory without gaps and without processing, providing a long capture buffer that can be post-processed an infinite number of times in an infinite number of ways to provide any type of gap-free results. Real-time bandwidth is fully as wide as the IF, and real-time analysis duration is limited only by memory size.
Both these real-time approaches have powerful benefits and complementary tradeoffs. The first one provides a virtually infinite duration of real-time results along with spectrum measurements that are always up to date. The second approach provides complete measurement flexibility (including vector measurements and demodulation) and a solution to the windowing problem to allow full measurement of every sample. It can thus be especially useful for transient and repeating signals.
Future posts will explore these tradeoffs in more detail, in the context of real world measurements. I’ll discuss dedicated real-time analyzers, other tools that perform real-time analysis, and some that do both.