Fft Analyzers - Agilent Technologies 89410A Operator's Manual

What Makes this Analyzer Different?

FFT analyzers

FFT spectrum analyzers (also referred to as dynamic signal analyzers) use digital
signal processing to sample the input signal and convert it to the frequency domain.
This conversion is done using the Fast Fourier Transform (FFT). The FFT is an
implementation of the Discrete Fourier Transform, the math algorithm used for
transforming data from the time domain to the frequency domain. This analyzer is
an example of an FFT analyzer that can make real-time measurements.
FFT spectrum analyzers are powerful instruments, since their processing power
can extract more information from an input signal than just the amplitude of
individual frequency components. For example, FFT analyzers can measure both
magnitude and phase, and can also switch easily between the time and frequency
domains. This makes them ideal instruments for the analysis of communication,
ultrasonic, and modulated signals.
If an FFT analyzer samples fast enough, all input data is evaluated and the analyzer
makes a real-time measurement. When operating in real time, FFT analyzers can
make the same measurements traditionally done with parallel-filter analyzers—and
make these measurements, if desired, with far greater frequency resolution.
In the past FFT analyzers have had the disadvantage of their restricted frequency
range—most FFT analyzers could not make measurements above 100 kHz. The
limiting factor has been the speed of the analog-to-digital converter used to sample
the analyzer's input signal. This is why swept-tuned superheterodyne analyzers are
still used for RF and microwave measurements, though some newer-generation
swept-tuned analyzers, such as the HP/Agilent 8560 family of analyzers can also
make FFT measurements. As you will see, this trend toward hybrid technology has
gone one step further with the Agilent 89400 Series Vector Signal Analyzers.
See the related sidebar for FFT background information.
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