Stanford Research Systems SR785, Руководство по эксплуатации и программированию

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2-16 FFT Measurements
SR785 Dynamic Signal Analyzer
FFT Measurements
Definitions
In the measurement definitions which follow, the following conventions are used. Angle
brackets <>, imply that the real and imaginary parts of the quantity within the brackets
are averaged with either linear or exponential weighting over some number of time
records. MAX() implies that the complex quantity inside the parentheses is replaced by
the maximum magnitude which that complex value takes over some number of time
records. The asterisk (*) is used to denote the conjugate of a complex quantity.
FFT Spectrum
The FFT spectrum is the basic measurement of an FFT analyzer. It is simply the FFT of a
time record. The FFT spectrum is a complex quantity (it contains phase as well as
amplitude information). This is sometimes referred to as the linear spectrum.
The phase of the spectrum is meaningful only if the time record is triggered with a fixed
relationship to the input signal. If the signal is repetitive as well (the signal and trigger
repeat), then vector averaging can be used to reduce the noise level of the spectrum. The
vector averaged spectrum is still a complex quantity.
The precise definition of the FFT1 measurement for all averaging modes is as follows:
No Average
FFT 1 = FFT1
Vector Average
FFT 1 = <FFT1>
RMS Average
FFT 1 =
√
<FFT1*• FFT1>
Peak Hold Average
FFT 1 =
√
MAX(FFT1*• FFT1)
Power Spectrum
The Power Spectrum is derived from the FFT spectrum by multiplying the spectrum by
its complex conjugate. The averaged power spectrum is a good approximation to the rms
signal and noise amplitudes. The power spectrum is a real quantity and contains no phase
information.
The precise definition of the Power Spectrum measurement for all averaging modes is as
follows:
No Average
Power Spectrum = FFT1*• FFT1
Vector Average
Power Spectrum = <FFT1>*• <FFT1>