Understanding Smart Sensors - Nomads.usp

Getting Sensor Information Into the MCU 87Table 4.2A/D Bits and Dynamic RangeA/D(Number of Bits)LSB Weight%ofFSLSB Voltagefor 5V FSDynamic Range(dB)4 6.25 300 mV 24.088 0.3906 19.5 mV 48.1610 0.0977 4.90 mV 60.1212 0.0244 1.20 mV 72.2514 0.00610 305 mV 84.2916 0.00153 75 mV 96.33theoretical root mean square (rms) signal-to-noise ratio for an N-bit ADC iscalculated bysignal-to-noise ratio = 602 . ⋅ N + 176 . dB(4.1)where N = number of bits.4.4.1 A/D ConvertersCommon A/D conversion techniques include single slope (ramp-integrating),dual slope integrating, tracking, successive approximation, folding (flash), andsigma-delta oversampled ADCs. Table 4.3 compares six types and lists the relativeconversion rate and relative silicon area required for each [24]. Note theeffect of hardware- versus software-driven successive approximation.Most ADCs can be classified into two groups based on the sampling rate,namely, Nyquist rate and oversampling converters. The Nyquist rate requiressampling the analog signals that have maximum frequencies slightly less thanthe Nyquist frequency, f N = f s /2, where f s is the sampling frequency. However,input signals above the Nyquist frequency cannot be properly converted andcreate signal distortion or aliasing. A low-pass antialiasing filter attenuates frequenciesabove the Nyquist frequency and keeps the response below the noisefloor.Sigma-delta (Σ-∆), or delta-sigma, converters are based on digital filteringtechniques and can easily be integrated with DSP ICs. Σ-∆ converters sample ata frequency much higher than the Nyquist frequency. Figure 4.13 shows the