RMS Averaging versus Vector Averaging

RMS averaging help smooth out signal fluctuations while vector averaging successfully reduces the noise floor. We can compare these results by calculating both averages on the same two-tone signal.

The following example compares the effect of RMS averaging and vector averaging on a typical signal. The input signal is a two-tone signal. The dominant tone is a 10 kHz sine wave with an amplitude of 1 Vp. The smaller component is a 15 kHz sine wave with an amplitude of 0.01 Vp. In addition to the tones, noise is present in the signal. The signal is sampled at 51.2 kHz in blocks of 1,000 samples. A Hanning window is applied to reduce leakage. The following figure shows the results of 100 averages.

Figure 36. RMS Averaging versus Vector Averaging

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The No Averaging plot identifies only the dominant tone.

The RMS Averaging plot does not reduce the noise floor. However, RMS averaging does smooth the noise out enough to unmask the tone at 15 kHz.

The Vector Averaging, Untriggered Acquisition plot underestimates the energy present at 10 kHz. Also, the tone at 15 kHz is indistinguishable from the noise.

The Vector Averaging, Triggered Acquisition plot accurately computes the energy of the tones, reduces the noise floor by 20 dB, and reveals the tone at 15 kHz. The 20 dB reduction in the noise floor corresponds to a factor of 10, or √100, where 100 is the number of averages completed.