Understanding Fft Plots

摘要

You can generate an FFT (fast-Fourier-transform) plot by periodically collecting a large number of conversion sam-ples from the output of an ADC. Typically, ADC manu-facturers use a single-tone, full-scale analog input signal for the performance curves in product data sheets. You take data from these conversions and create a plot similar to the one in Figure 1. The frequency scale of this plot is always linear, from zero to the converter's sampling frequency divided by two.rnYou generate the plot by applying a sampling frequency of 100k samples/ sec to a 12-bit ADC with an analog input signal of 9.9 kHz. The signal at 9.9 kHz is the fundamental input signal (A). The fundamental input-signal spur reaches almost 0 dB.rnThe specifications of interest in an FFT plot are the fundamental input signal, the SNR (signal-to-noise ratio), the THD (total harmonic distortion), and the average noise floor. A useful way of determining noise in an ADCrncircuit is with the SNR (B), the ratio of signal power to noise power. The SNR of the FFT calculation is a combination of several noise sources, including the quantization error of the ADC, the internal noise of the ADC, noise from the voltage reference, and noise from the driving amplifier.