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.
Anti Aliasing
Input Signal Conditioning
Input signal conditioning techniques remove frequency components above the Nyquist limit to prevent data corruption during sampling. The primary function of anti aliasing is to ensure that every recorded value accurately represents a signal within the defined measurement bandwidth. Components at higher frequencies are filtered out before they reach the analog to digital converter.
Analog Filtering
Low pass hardware filters provide the most common method for achieving this frequency restriction. These circuits sit between the sensor and the digitizer to attenuate signals that would otherwise fold back into the lower frequency range. Passive RC filters or active Butterworth designs are selected based on the required roll off and phase linearity.
Digital Decimation
Modern architectures often use oversampling followed by digital processing to refine the filtering process. Once the signal is digitized at a high rate, anti aliasing continues through mathematical algorithms that average samples and reduce the effective data rate. This hybrid approach allows for much sharper filter transitions than analog components alone can provide while reducing the overall noise floor.
Performance Verification
Verification of the filter stage requires measuring the flatness of the response across the entire intended passband. Anti aliasing must not attenuate the signal.