6 Common FFT Follies

Figure 6-1, Figure 6-2, and Figure 6-3 emphasize some invalid FFT data captures that can lead to an inaccurate understanding of ADC performance. Our aim is to aid those designers new to ADC testing from an evaluation module or a system-level design standpoint who use FFT data captures to determine the overall performance of a signal-chain design.

The first FFT signature type is known as an FFT burp, illustrated in Figure 6-1. This FFT signature shows a wide skirt around the fundamental frequency and occurs when the designer intends to coherently sample but does not have the correct analog input frequency, or uses incorrect calculations. Notice that the SNR/SFDR performance is far from the ADC’s data sheet performance specification.

Figure 6-2 shows another FFT signature type called the FFT picket-fence effect, which occurs when the user is almost accurate noncoherently sampling at the exact same place along the analog input signal. The issue here is that the analog input frequency is not a prime number, and therefore is not smeared enough in frequency to walk along the input signal at various points. In this case, the Fs = 5,200MSPS and the analog frequency is exactly 1000.0000MHz, which is not prime. Using a prime number like 1011.1235MHz, for example, can make sure enough smearing to accurately sample the analog input signal.

The third signature type is called FFT binning. FFT binning is similar to an FFT picket fence, but is a direct multiple of the sampling rate. For example, as shown in Figure 6-3, Fs = 5,200MSPS and the analog input frequency is exactly one-fifth the sample frequency, or 1040.0000MHz.

What happens here is that, again, the same points along the analog input signal are sampled, but at such a rate that all of the harmonics fold on top each other – HD2 and HD3 in Figure 6-3, as well as the fundamental and HD4. You can easily fix the FFT binning effect by using a random prime number such as 1041.1359MHz.