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AD9022AZ Arkusz danych(PDF) 8 Page - Analog Devices |
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AD9022AZ Arkusz danych(HTML) 8 Page - Analog Devices |
8 / 12 page –8– AD9022 REV. B This will be true only for converters in which perfect quantiza- tion noise dominates. There may be an upper sample rate, above which the thermal noise of the converter is the dominant source of noise. In this case, normalization would be based on the noise bandwidth of the ADC. For an AD9022 with a typical SNR of 64 dB and a sample rate of 20 MSPS, the normalized SNR is equal to 134 dB (64 + 70). Both thermal and quantiza- tion noise contribute to this number. The SNR of the input is assumed to be limited by the thermal noise of the input resistance, or –174 dBm/Hz. The input signal level is +10 dBm (2 V p-p into 50 Ω). Noise figure of the ADC can be calculated by: NF = SNR (in) – SNR (out) = [+10 – (174)] – 134 = 50 dB Most ADCs detect input voltage levels, not power. Conse- quently, the input SNR can be determined more accurately by determining the ratio of the signal voltage to the noise voltage of the terminating resistor. However, both the input signal and noise voltage delivered to the ADC are also a function of the source impedance. The dependence of NF on sample rate, linearity, source and terminating impedances, and the number of assumptions required, highlight the weakness of using NF as a figure of merit for an ADC. The rather large number that results bolsters this belief by indicating the ADC is often the weakest link in the signal processing path. Linearity The Third Order intercept point for a linear device (with some nonlinearity) is a good way to predict 3rd order spurious signals as a function of input signal level. For an ADC, however, this in an invalid concept except with signals near full scale. As the input signal is reduced, the performance burden shifts from the input track-and-hold (T/H) to the encoder. This creates a non- linear function, as contrasted with the third order intercept behavior, which predicts an improvement in dynamic range as the signal level is decreased. For signals near full scale, the intercept point is calculated the same as any device: Intercept Point = [Harmonic Suppression/(N –1)] + Input Power where N = the order of the IMD (3 in this case) AD9022 Intercept Point = 80/2 + 3 dBm (7 dBm below full scale) = 43 dBm For signals below this level, the spurious free dynamic range (SFDR) curves shown in the data sheet are a more accurate predictor of dynamic range. The SFDR curve is generated by measuring the ratio of the signal (either tone in the two-tone measurement) to the worst spurious signal, which is observed as the analog input signal amplitude is swept. The worst spurious signal is usually the second harmonic or 3rd order IMD. Actual results are shown on several plots. The straightline with a slope of one is constructed at the point where the worst SFDR touches the line. This line, extrapolated to full scale, gives the SFDR of the ADC. This value can then be used to predict the dynamic range by simply subtracting the input level from the SFDR. It should be noted that all SFDR lines are constructed to be valid only below a certain level below full scale. Above these points, the linearity of the device is dominated by the nonlinearities of the front end and best predicted by the intercept point. AD9022 NOISE PERFORMANCE High speed, wide bandwidth ADCs such as the AD9022 are optimized for dynamic performance over a wide range of analog input frequencies. However, there are many applications (Imag- ing, Instrumentation, etc.) where dc precision is also important. Due to the wide input bandwidth of the AD9022 for a given input voltage, there will be a range of output codes which may occur. This is caused by unavoidable circuit noise within the wideband circuits in the ADC. If a dc signal is applied to the ADC and several thousand outputs are recorded, a distribution of codes such as that shown in the histogram below may result. OUTPUT CODE 2.0 –2.0 –1.0 –1.5 x–3 0 –0.5 0.5 1.0 1.5 ONE STANDARD DEVIATION = RMS NOISE LEVEL x–2 x–1 x x+1 x+2 x+3 Figure 11. ADC Equivalent Input Noise The correct code appears most of the time, but adjacent codes also appear with reduced probability. If a normal probability density curve is fitted to this Gaussian distribution of codes, the standard deviation will be equal to the equivalent input rms noise of the ADC. The rms noise may also be approximated by converting the SNR, as measured by a low frequency FFT, to an equivalent input noise. This method is accurate only if the SNR performance is dominated by random thermal noise (the low frequency SNR without harmonics is the best measure). Sixty-three dB equates to 1 LSB rms for a 2 V p-p (0.707 V rms) input signal. The AD9022 has approximately 0.5 LSB of rms noise or a noise limited SNR of 69 dB, indicating that noise alone does not limit the SNR performance of the device (quanti- zation noise and linearity are also major contributors). This thermal noise may come from several sources. The drive source impedance should be kept low to minimize resistor thermal noise. Some of the internal ADC noise is generated in the wideband T/H. Sampling ADCs generally have input band- widths which exceed the Nyquist frequency of one-half the sampling rate. (The AD9022 has an input bandwidth of over 100 MHz, even though the sampling rate is limited to 20 MSPS.) Wide bandwidth is required to minimize gain and phase distor- tion and to permit adequate settling times in the internal ampli- fiers and T/Hs. But a certain amount of unavoidable noise is generated in the T/H and other wideband circuits within the ADC; this causes variation in output codes for dc inputs. Good layout, grounding and decoupling techniques are essential to prevent external noise from coupling into the ADC and further corrupting performance. |
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