Thursday, April 23, 2009
Airmagnet Spectrum Analyzer
AirMagnet's Spectrum Analyzer proactively identifies, classifies, and finds sources of RF interferences that impact the performance of Wi-Fi networks. Unlike earlier generations of spectrum analyzers, AirMagnet's Spectrum Analyzer provides an IT-friendly user interface. The system automatically identifies the specific types of devices that are causing RF interference and tracks them to their physical location, enabling network managers to resolve issues quickly and easily.
Superheterodyne Spectrum Analyzer
General Instructions
This spectral simulation is an interactive Java applet. You can change parameters by clicking on the vertical arrow keys. The five control buttons at the lower right are used to start (triangle) and pause (square) the simulation, to skip forward or back one section at a time (double triangles), and to change speed (+ and -).
After the simulation is complete, the start button takes you back to the beginning of the simulation. You may experience a delay at this point.
A spectrum analyzer is an extremely useful measurement tool that can show, in the frequency domain, information not readily recognizable with a time domain instrument such as an oscilloscope. For example, the frequency content of a signal (e.g. a fundamental sinusoid and one or more harmonic components) is readily identified with a spectrum analyzer, something difficult to identify from an oscilloscope display.
The most common type of spectrum analyzer, especially at high radio frequency and microwave frequencies is the Superheterodyne Spectrum Analyzer, shown in the simplified block diagram below. It operates in a fashion similar to a superheterodyne AM radio receiver, with the output in this case going to a CRT display rather than a speaker.
This spectral simulation is an interactive Java applet. You can change parameters by clicking on the vertical arrow keys. The five control buttons at the lower right are used to start (triangle) and pause (square) the simulation, to skip forward or back one section at a time (double triangles), and to change speed (+ and -).
After the simulation is complete, the start button takes you back to the beginning of the simulation. You may experience a delay at this point.
A spectrum analyzer is an extremely useful measurement tool that can show, in the frequency domain, information not readily recognizable with a time domain instrument such as an oscilloscope. For example, the frequency content of a signal (e.g. a fundamental sinusoid and one or more harmonic components) is readily identified with a spectrum analyzer, something difficult to identify from an oscilloscope display.
The most common type of spectrum analyzer, especially at high radio frequency and microwave frequencies is the Superheterodyne Spectrum Analyzer, shown in the simplified block diagram below. It operates in a fashion similar to a superheterodyne AM radio receiver, with the output in this case going to a CRT display rather than a speaker.
Wednesday, April 15, 2009
Spectrum analyzer
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.
There are analog and digital spectrum analyzers:
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.
There are analog and digital spectrum analyzers:
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.
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 low noise floor near the physical thermal noise limit of -174 dBm.
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 low noise floor near the physical thermal noise limit of -174 dBm.
Acoustic uses
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.
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.
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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