Aligning Moving Average Windows with Converters to Eliminate Aliasing Artifacts
Aligning moving average window lengths to match converter sample periods places exact spectral nulls over periodic interference to eliminate aliasing artifacts.
Aliasing Artifacts
Signal Distortion
Spurious signal components arise in sampled data when the input frequency exceeds the folding limit of the digitization system. These aliasing artifacts degrade the fidelity of the acquired waveform by masquerading as legitimate lower-frequency signals. Measurement systems are limited by their sampling rate, which defines the boundary where high-frequency noise becomes indistinguishable from the primary signal.
Frequency Mapping
Frequency translation formulas map the out-of-band signals into the first Nyquist zone. This mapping creates aliasing artifacts that are difficult to distinguish from real inputs. Processing algorithms cannot separate these mirrored signals from the original spectrum once they are acquired.
Filter Strategy
Anti-aliasing filters prevent the intrusion of high-frequency components by attenuating all signals above the Nyquist threshold before discretization occurs. In analog-to-digital converters, the transition band of these filters must be steep enough to suppress unwanted signals. System architects often use oversampling to ease the design of the analog filter, spreading the quantization noise over a wider spectrum.
This digital technique permits a simpler, more cost-effective analog front-end.
Testing Protocol
Verification of signal purity involves feeding a pure sinusoidal test tone into the system and checking for unwanted spectral lines. A high-resolution spectrum analyzer identifies any misplaced frequency peaks that indicate aliasing artifacts.