A spectrum analyzer or spectral analyzer is a device used to examine the spectral composition of some electrical, acoustic, or optical waveform. It may also measure the power spectrum.
- An analog spectrum analyzer uses either a variable band-pass 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 discrete Fourier transform (DFT), a mathematical process that transforms a waveform into the components of its frequency spectrum.
Some spectrum analyzers (such as "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 fast fourier transformation (FFT) techniques.
Spectrum-analyzer functions
Frequency
Allows one to fix the window of frequencies to visualize
Marker/peak search
Controls the position and function of markers and indicates the value of power.
Bandwidth/average
Is a filter of resolution. The spectrum analyzer captures the measure on having displaced a filter of small bandwidth along the window of frequencies.
Amplitude
Is the maximum value of a signal in a point.
View/trace
Manages parameters of measurement. It stores the maximum values in each frequency and a solved measurement to compare it.
Operation
Usually, a spectrum analyzer displays a power spectrum over a given frequency range, 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 were not present in the original signal. A new method, without using a high local oscillator (LO) (that usually produces a high-frequency signal close to the signal) is used on the latest analyzer generation like Aaronia´s Spectran series. The advantage of this new method is a very lownoise floor near the physical thermal noise limit of -174 dBm.
Acoustic uses
In acoustics, the spectrum analyzer is also referred to as a spectrograph, and it 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 andaudiology research, before eventually being superseded by digital signal processing techniques.
The modern day acoustic spectrograph, or spectrum analyzer benefits from the advancements made in the capabilities of personal computers. The relatively low frequency content of common acoustic signals such as speech or music (typically between 0 and 20 kHz) can be sampled with the existing sound card hardware built in to most personal computers. Since specialized hardware is not required, an acoustic spectrum analyzer can be fully implemented in software. Unlike radio frequency spectrum analyzers, software based audio spectrum analyzers are available at low cost, providing easy access not only to industry professionals, but also to academicians, students and the lay hobbyist.
The acoustic spectrogram generated by the spectrum analyzer provides an acoustic signature of the source. The acoustic signature of human speech can be characterized and used to identify the originator. This is of particular interest in the fields of law enforcement and forensic analysis. Similarly, analysis of the acoustic signature of a musical instrument may be used to characterize the sometimes subtle differences between a fine instrument and one that might be considered more mediocre.
RF uses
Spectrum analyzers are widely used to measure the frequency response, noise and distortion characteristics of all kinds of RF circuitry, by comparing the input and output spectra.
In telecommunications, spectrum analyzers are used to determine occupied bandwidth and track interference sources. Cellplanners use this equipment to determine interference sources in the GSM/TETRA and UMTS technology.
In EMC testing, spectrum analyzers may be used to characterise test signals and to measure the response of the equipment under test.
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