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.
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.