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What is a spectrum analyzer used for?



A spectrum analyzer measures the magnitude of an input signal versus frequency within the full frequency range of the instrument. The primary use is to measure the power of the spectrum of known and unknown signals.

What is a Spectrum Analyzer & What Does it Do? 

A spectrum analyzer measures the magnitude of an input signal versus frequency within the full frequency range of the instrument. The primary use is to measure the power of the spectrum of known and unknown signals. Given the challenge of characterizing the behavior of today’s RF devices, it is necessary to understand how frequency, amplitude, and modulation parameters behave over short and long intervals of time.

Traditional tools like Swept Spectrum Analyzers (SA) and Vector Signal Analyzers (VSA) provide snapshots of the signal in the frequency domain or the modulation domain. This is often not enough information to confidently describe the dynamic nature of modern RF signals. To overcome these evolving challenges, it is crucial for today’s engineers and scientists to be able to reliably detect and characterize RF signals that change over time, something not easily done with traditional measurement tools.

The Real-time Spectrum Analyzer (RSA) is an instrument that can discover elusive effects in RF signals, trigger on those effects, seamlessly capture them into memory, and analyze them in the frequency, time, modulation, statistical and code domains.

As RF signals have become ubiquitous in the modern world, so too have problems with interference between the devices that generate them. To overcome evolving challenges, it is crucial for today’s engineers and scientists to be able to reliably detect and characterize RF signals that change over time, something not easily done with traditional measurement tools.

One such measurement tool that’s evolved to keep up is the Real-Time Spectrum Analyzer. A real-time spectrum analyzer can help with most modern RF measurement challenges, like: discovery of rare, short deration events; seeing weak signals masked by stronger ones; observing signals masked by noise, finding and analyzing transient and dynamic signals; capturing burst transmissions, glitches, switching transients, to just name a few.