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.
Nyquist Frequency
Sampling Boundary
Discrete-time signal processing requires a sampling rate that is at least twice the highest frequency component of the input signal to prevent distortion. This Nyquist frequency acts as the boundary limit where the signal can still be reconstructed without error. It establishes the baseline configuration for all digital data acquisition systems, defining the bandwidth of the system.
Aliasing Protection
Frequency components that exceed the Nyquist frequency fold back into the passband and appear as low-frequency noise. This foldback is prevented by implementing an analog low-pass filter before the sampling stage. This anti-aliasing filter attenuates the high-frequency components that would otherwise distort the digital measurement.
Dynamic Range
Oversampling involves sampling the analog signal at a rate much higher than the Nyquist frequency to distribute the quantization noise over a broader band. This digital technique permits the use of a simpler analog filter and improves the effective resolution of the converter through subsequent digital filtering. The signal is then downsampled to the desired output rate, preserving the dynamic range while minimizing data storage requirements.
Spectral Measurement
High-frequency spectrum analyzers must operate with a sampling clock that provides a margin above the target frequency. This headroom ensures that the measurement remains accurate.