Configuring Moving Average Filter Lengths for Decimated Signal Processing
Matching moving average filter length to the decimation factor eliminates alias leakage by placing transfer function zeros directly on downsampling fold points.
Downsampling
Rate Reduction
Digital signal processing uses the reduction of the sampling rate of a discrete signal to decrease the computational load of subsequent stages. The process of downsampling decreases the density of the sampled data by retaining only every Nth sample. This action optimizes the flow of data through digital filters and processor cores.
Decimation Stage
Sampling rate alteration occurs in a multi-rate digital system by combining anti-aliasing filtering with sample removal. Removing samples without filtering leads to aliasing, which ruins the integrity of the original data. A digital low-pass filter must remove high-frequency components that lie above the new Nyquist frequency.
Alias Avoidance
Frequency folding occurs when the original signal contains frequencies higher than half of the target sampling rate. To avoid this degradation, the input signal is processed by an anti-aliasing filter before the sample discarding step. The filter must exhibit a sharp transition band and deep stopband attenuation to protect the baseband signal.
In typical processing systems, a finite impulse response filter executes this task with high phase linearity. High-resolution sensors rely on this filtering to preserve accuracy during decimation in delta-sigma converters. The filter coefficients are calibrated during design to ensure that the passband ripple remains below a specified tolerance level, preventing amplitude distortion across the signal band.
Signal Degradation
Incomplete filtering before rate reduction introduces irreversible distortion that mimics genuine sensor signals. The resulting error cannot be removed by subsequent digital processing. Systems verify the integrity of the output by comparing the signal-to-noise ratio before and after the rate reduction.