The FFT analyzer technology is the less commonly used on its own, but it is able to offer some distinct advantages over the more common swept frequency analyzer. By combining the two technologies the advantages of each can be utilized to offer extremely high performance items of test equipment.

In general, spectrum analyzers are used to provide a view of radio frequency, or in some case audio frequency waveforms in the time domain. With other instruments able to provide views of other aspects of signals, the spectrum analyzer is uniquely placed to offer views of the spectrum of a signal, revealing aspects that other instruments are unable to do. With the FFT analyzer able to provide facilities that cannot be provided by swept frequency analyzers (improper sentence formation), enabling fast capture and forms of analysis that are not possible with sweep / super heterodyne techniques alone.

Analogue front end attenuators / gain:

The FFT analyzer requires attenuators of gain stages to ensure that the signal is at the right level for the analogue to digital conversion. If the signal level is too high, then clipping and distortion will occur, too

low and the resolution of the ADC and noise become a problems. Matching the signal level to the ADC range ensures the optimum performance and maximizes the resolution of the ADC.

Analogue low pass anti-aliasing filter:

The signal is passed through an anti-aliasing filter. This is required because the rate at which points are taken by the sampling system within the FFT spectrum analyzer is particularly important. The waveform must be sampled at a sufficiently high rate. According to the Nyquist theorem a signal must be sampled at a rate equal to twice that of the highest frequency, and also any component whose frequency is higher than the Nyquist rate will appear in the measurement as a lower frequency component - a factor known as "aliasing". This results from the where the actual values of the higher rate fall when the samples are taken. To avoid aliasing a low pass filter is placed ahead of the sampler to remove any unwanted high frequency elements. This filter must have a cut-off frequency which is less than half the sampling rate, although typically to provide some margin, the low pass filter cut-off frequency is at highest 2.5 times less than the sampling rate of the FFT spectrum analyzer. In turn this determines the maximum frequency of operation of the FFT spectrum analyzer.

Sampling and analogue to digital conversion:

In order to perform the analogue to digital conversion, two elements are required. The first is a sampler which takes samples at discrete time intervals - the sampling rate. The importance of this rate has been discussed above. The samples are then passed to an analogue to digital converter which produces the digital format for the samples that is required for the FFT analysis.

FFT analyzer:

With the data from the sampler, which is in the time domain, this is then converted into the frequency domain by the FFT analyzer. This is then able to further process the data using digital signal processing techniques to analyze the data in the format required.

Display:

With the power of processing it is possible to present the information for display in a variety of ways. Today's displays are very flexible and enable the information to be presented in formats that are easy to comprehend and reveal a variety of facets of the signal. The display elements of the FFT spectrum analyzer are therefore very important so that the information captured and processed can be suitably presented for the user.