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overview
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There are six commonly used indicators for quantitatively expressing the dynamic performance of ADCs, namely: SINAD (signal-to-noise ratio), ENOB (effective number of bits), SNR (signal-to-noise ratio), THD (total harmonic distortion), THD+N ( Total Harmonic Distortion Plus Noise) and SFDR (Spurious Free Dynamic Range). For these specifications, although most ADC manufacturers use the same definition, there are some exceptions. These metrics are important when comparing ADCs, so it's important to understand not only what aspects of performance each metric reflects, but how they relate to each other.
overall architecture process
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There are several ways to quantify the distortion and noise of an ADC, but all are based on an FFT analysis using a generalized test setup, such as the one shown in Figure 1.
Explanation of technical terms
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ADC:
Analog-to-digital converter, or A/D converter, or ADC for short, usually refers to an electronic component that converts an analog signal into a digital signal. A common analog-to-digital converter converts an input voltage signal into an output digital signal. Since the digital signal itself has no practical significance, it only represents a relative size. Therefore, any analog-to-digital converter needs a reference analog quantity as a conversion standard, and the more common reference standard is the largest convertible signal size. The output digital quantity represents the magnitude of the input signal relative to the reference signal
technical details
The spectrum output of FFT is M/2 continuous points in the frequency domain (M is the size of FFT, that is, the number of sampling points stored in the buffer memory). The spacing between the two points is fs/M, and the total frequency range covered is DC to fs/2, where fs is the sampling rate. The width of each frequency "bin" (sometimes called the "resolution" of the FFT) is fs/M. Figure 2 shows the FFT output of an ideal 12-bit ADC using the Analog Devices ADIsimADC® program. Note that the theoretical noise floor of the FFT is equal to the theoretical SNR plus the FFT "processing gain" of 10×log(M/2). It must be remembered that the noise value used to calculate the SNR is the noise distributed over the entire Nyquist bandwidth (DC to fs/2), whereas the FFT is used as a narrowband spectrum analyzer with a bandwidth of fs/M that sweeps the entire spectrum , which results in pushing the noise down by an amount equal to the processing gain, an effect identical to the bandwidth-narrowing of an analog spectrum analyzer. The FFT data shown in Figure 2 represent the average of 5 independent FFTs. Note that averaging multiple FFTs will not affect the average noise floor, it will only "smooth out" the effect of random variations in the amplitudes contained in each frequency bin.
The FFT output can be used like an analog spectrum analyzer to measure the magnitude of individual harmonics and the noise content of the digitized signal. Harmonics of the input signal can be distinguished from other distortion products by their position in the frequency spectrum. Figure 3 shows a 7MHz input signal sampled at 20MSPS and the location of the first 9 harmonics. The aliased harmonic of fa is at the frequency position of |±Kfs±nfa|, where n is the order of the harmonic, K=0,1,2,3,.... Data sheets generally only state the second and third harmonics, since these tend to be the largest, but some data sheets state values for the worst harmonics. Harmonic distortion is usually expressed in dBc (decibels below the carrier), although audio applications may express it as a percentage, which refers to the ratio of the rms value of the signal to the rms value of the associated harmonic. Harmonic distortion is typically specified with an input signal close to full scale (typically 0.5-1dB below full scale to prevent clamping), but can be specified at any level. For signals well below full-scale, other distortion products—not direct harmonics—caused by the converter's differential nonlinearity (DNL) can limit performance.
summary
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Total Harmonic Distortion (THD) refers to the ratio of the root mean square value of the fundamental signal to the average value of the sum square root of its harmonics (generally only the first 5 harmonics are more important). Although the THD of an ADC can be specified by any level, it is generally specified by an input signal close to full scale. Total Harmonic Distortion Plus Noise (THD) refers to the ratio of the root mean square value of the fundamental signal to the average value of the root sum square of its harmonics plus all noise components (except DC). The bandwidth of the noise measurement must be stated. For FFT, the bandwidth is from DC to fs/2. If the measurement bandwidth is from DC to fs/2 (Nyquist bandwidth), then THD+N is equal to SINAD as described below. Note, however, that in audio applications, the measurement bandwidth is not necessarily the Nyquist bandwidth. Spurious-free dynamic range (SFDR) refers to the ratio of the rms value of a signal to the rms value of the worst spurious signal, no matter where it is located in the spectrum. The worst spurs may or may not be harmonics of the original signal. In communication systems, SFDR is an important metric because it represents the minimum signal value that can be distinguished from large interfering signals (blocking signals). SFDR can be specified relative to full scale (dBFS) or actual signal amplitude (dBc). Figure 4 graphically illustrates the definition of SFDR.