Spectrum analyzer

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A Rohde & Schwarz FSH3 spectrum analyzer
A Rohde & Schwarz FSH3 spectrum analyzer

A spectrum analyzer is a device used to examine the spectral composition of some electrical, acoustic, or optical waveform.

Often, it measures the power spectrum.

There are analog and digital spectrum analyzers:

  • An analog spectrum analyzer uses either a variable bandpass filter whose mid-frequency is automatically tuned (shifted, swept) through the range of frequencies of which the spectrum is to be measured or a superheterodyne receiver where the local oscillator is swept through a range of frequencies.
  • A digital spectrum analyzer computes the Fast Fourier transform (FFT), a mathematical process that transforms a waveform into the components of its frequency spectrum.

Some spectrum analyzers (such as Tektronix's family of "real-time spectrum analyzers") use a hybrid technique where the incoming signal is first down-converted to a lower frequency using superheterodyne techniques and then analyzed using FFT techniques.

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Usually, a spectrum analyzer displays a power spectrum over a given frequency range in real time, changing the display as the properties of the signal change. There is a trade-off between how quickly the display can be updated and the frequency resolution, which is for example relevant for distinguishing frequency components that are close together. With a digital spectrum analyzer, the frequency resolution is Δν = 1 / T, the inverse of the time T over which the waveform is measured and Fourier transformed. With an analog spectrum analyzer, it is dependent on the bandwidth setting of the bandpass filter. However, an analog spectrum analyzer will not produce meaningful results if the filter bandwidth (in Hz) is smaller than the square root of the sweep speed (in Hz/s), which means that an analog spectrum analyzer can never beat a digital one in terms of frequency resolution for a given acquisition time. Choosing a wider bandpass filter will improve the signal-to-noise ratio at the expense of a decreased frequency resolution.

With Fourier transform analysis in a digital spectrum analyzer, it is necessary to sample the input signal with a sampling frequency νs that is at least twice the highest frequency that is present in the signal, due to the Nyquist limit. A Fourier transform will then produce a spectrum containing all frequencies from zero to νs / 2. This can place considerable demands on the required analog-to-digital converter and processing power for the Fourier transform. Often, one is only interested in a narrow frequency range, for example between 88 and 108 MHz, which would require at least a sampling frequency of 216 MHz, not counting the low-pass anti-aliasing filter. In such cases, it can be more economic to first use a superheterodyne receiver to transform the signal to a lower range, such as 8 to 28 MHz, and then sample the signal at 56 MHz. This is how an analog-digital-hybrid spectrum analyzer works.

For use with very weak signals, a pre-amplifier can be used, although harmonic and intermodulation distortion may lead to the creation of new frequency components that weren't present in the original signal.

Acoustic spectrogram of Tokyo Japanese [minato]
Acoustic spectrogram of Tokyo Japanese [minato]
Real Time Analysis
A real time analysis of a song; this spectrum analyzer output features frequency on X, magnitude on Y, and moves through time in sequence with the song.
Wikipedia:Media help

In acoustics, a spectrograph converts a sound wave into a sound spectrogram. The first acoustic spectrograph was developed during World War II at Bell Telephone Laboratories, and was widely used in speech science, acoustic phonetics and audiology research, before eventually being superseded by digital signal processing techniques. Now spectrum analyzers cover the acoustic range.

Used to measure atomic particles.

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