Aliasing
When you take a set of samples from an input signal, any frequency in the input signal which is above the Nyquist frequency (half the sampling rate), appears to be at a frequency below the Nyquist frequency. This phenomenon is called aliasing.
For example, with a frequency of 20,000 samples per second, the Nyquist frequency is 10,000 Hz. If the input signal contains a component at 11,000 Hz, it will appear at 9,000 Hz.
It is easy to check for aliasing by changing the sampling frequency: real signals will stay at the same frequency, whereas aliased signals will move.
It is possible to reduce the effects of aliasing by taking several readings for each sample (oversampling), then applying a digital filter to attenuate signals above the Nyquist frequency. Note: This is only possible when the sampling rate is well below the maximum sampling rate at which the ADC can operate.
When you take a set of samples from an input signal, any frequency in the input signal which is above the Nyquist frequency (half the sampling rate), appears to be at a frequency below the Nyquist frequency. This phenomenon is called aliasing.
For example, with a frequency of 20,000 samples per second, the Nyquist frequency is 10,000 Hz. If the input signal contains a component at 11,000 Hz, it will appear at 9,000 Hz.
It is easy to check for aliasing by changing the sampling frequency: real signals will stay at the same frequency, whereas aliased signals will move.
It is possible to reduce the effects of aliasing by taking several readings for each sample (oversampling), then applying a digital filter to attenuate signals above the Nyquist frequency. Note: This is only possible when the sampling rate is well below the maximum sampling rate at which the ADC can operate.