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New feature for the 44xx series: Boxcar Average | Spectrum

Boxcar function smooths out noise to give clear signal
The Boxcar averaging function smooths out high frequency noise to give a clear signal. It is most useful in situations where signals have been oversampled and it can be used to increase vertical resolution, lower noise and improve dynamic characteristics such as signal-to-noise ratio (SNR) and spurious free dynamic range (SFDR). It uses a mathematical signal processing function to effectively recalculate the vertical value of each acquired data point by averaging it with adjacent sample points.

Boxcar averaging is an excellent tool for improving the measurement performance of high-speed high-resolution digitizers. By taking advantage of situations where signals have been oversampled, the function delivers a number of clear benefits. Not only does Boxcar averaging reduce the effect of high frequency noise but it also improves results in low noise level situations. For example, on high purity signals our own tests have shown that a digitizer’s performance, as measured by its effective number of bits (ENOB), can be improved by at least 2 Bits when using Boxcar averaging. SFDR and SNR measurements are also better by more than 12 dB.

To allow maximum flexibility, the Boxcar function allows users to select the number of adjacent points to be averaged from 2 to 256. The averaged data is subsequently stored with higher resolution by an amount that is proportional to the number of points selected. For example, selecting two adjacent points would increase the resolution of a 16 Bit digitizer to that equivalent to 17 Bits, selecting four adjacent points equates to 18 Bits and selecting the maximum 256 points would produce a theoretical 24 Bits.

The downside of Boxcar averaging is that the averaged waveforms are effectively filtered so that some high-frequency signal content may be lost.  However, if the signals of interest are at frequencies well below the sampling rate of the digitizer, then the technique offers a number of advantages.  For example, unlike traditional averaging methods, Boxcar averaging works for single shot acquisitions without the need for multiple trigger events or a repeatable signal. Boxcar averaged waveforms are also decimated (by the averaging factor) so that stored waveforms are reduced in size and can be transferred and processed faster. Even though the resulting waveforms are decimated, the Spectrum implementation makes sure that the trigger detection is still running with full sampling speed so that there is always a very precise timing relationship between the averaged signal and the trigger position.