Oversampling Topology
Analog-to-digital signal transformation architectures utilize high-frequency single-bit or multi-bit quantizers to trade sampling speed for amplitude resolution. Integrating a delta sigma converter operates by oversampling input signals well above the Nyquist rate and shifting quantization noise to higher frequencies outside the measurement band. Integrating amplifiers inside a negative feedback loop force quantization errors into high-frequency spectral regions.
Digital filtering subsequent to quantization removes out-of-band noise while reducing sample rate.
Noise Shaping
Feedback topologies dictate noise shaping transfer functions within loop integrators. Higher modulator orders push quantization noise steeper into high frequencies, allowing lower oversampling ratios for equivalent dynamic range. Loop stability requirements constrain modulator gain coefficients under full-scale input swings.
Decimation Filtering
Digital decimation filters aggregate high-speed bitstreams into high-resolution multi-bit words at lower output sample rates. Finite impulse response filters attenuate high-frequency noise while providing linear phase across the passband. Phase linearity preserves temporal characteristics of sensor signals.
Resolution Threshold
Signal-to-noise performance depends directly on oversampling ratio and modulator order. A delta sigma converter achieves up to twenty-four bits of noise-free resolution for low-bandwidth sensor applications. Clock jitter on modulator sampling signals degrades high-frequency signal-to-noise ratio by introducing phase noise into the feedback loop.
