Applying an Anti-Aliasing Filter (Advanced Signal Processing Toolkit or Control Design and Simulation Module)

According to the Nyquist sampling theorem, the sampling rate must be greater than twice the maximum frequency component of the signal of interest. In other words, the maximum frequency of the input signal must be smaller than half the sampling rate. For example, if the maximum frequency component of a signal is 1K Hz, the sampling rate must be greater than 2K Hz. In real-world applications, you can set the sampling rate between 3K and 5K Hz.

This criterion, in practice, is often difficult to ensure. Even if you are sure that the measured signal has an upper limit on its frequency, external factors, such as signals from the powerline interference or radio stations, can contain frequencies higher than the Nyquist frequency. These frequencies might then alias into the frequency range of interest and give you inaccurate results.

To ensure that you limit the frequency content of the input signal, you can add a lowpass filter before the sampler and the analog to digital converter (ADC). A lowpass filter passes low frequencies and attenuates high frequencies. This filter is an anti-aliasing filter because by attenuating the frequencies greater than the Nyquist frequency, the filter prevents the sampling of aliased components. When you use a filter before the sampler and ADC, the anti-aliasing filter is an analog filter with a proper cut-off frequency. The cut-off frequency equals the maximum frequency component of the signal of interest. Using the anti-aliasing filter satisfies the Nyquist sampling theorem. You must have data acquisition hardware that supports anti-aliasing filters to use this filter.

Similarly, you can use a digital filter to remove frequency content above the system bandwidth and then downsample the data to the desired sampling rate.