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sampling rates up to 6.4 GS/s, 12-bit resolution and data streaming rates up to 12.8 GB/s over the PCIe 16 lane Gen3 interface

SUMMATION AVERAGING SYSTEM Advanced FPGA-based averaging system

Oct 31, 2022

To perform on-board summation averaging, high-speed M5i digitizer cards function by utilising advanced, on-board Field Programmable Gate Array (FPGA) technology. Doing this creates a unique offering as the M5i series digitizers deliver real-time sampling at rates up to 6.4 GS/s with 12-bit resolution, and they can stream all the acquired data directly over the PCIe bus at a record-breaking 12.8 GB/s. This powerful tool reduces signal noise and improves resolution and dynamics, and it further enhances the new firmware option, which permits acquired signals to be averaged at an astonishing rate of 15 million events per second.

A new firmware option has been created by Spectrum Instrumentation that allows the company’s high-speed M5i digitizer cards (figure 1) to perform onboard summation averaging. Averaging is a useful tool for reducing unwanted signal noise while at the same time improving measurement resolution, dynamic range, and signal-to-noise ratio (SNR). This new option for the M5i series makes for one of the most powerful averaging systems available today. The FPGA-based processing allows ultrafast averaging, even on complex and long waveforms. In fact, there’s enough processing power available to average waveforms that contain as many as 1 MSample per acquisition. The result is an averaging package that will be of interest to anybody working with high-frequency signals or very narrow pulses that are low-level or where signal details are being lost due to high amounts of noise. This includes applications such as mass spectrometry, lidar, radio astronomy, automation, radar, biomedicine, nuclear physics, communications, sonar, and many more.

Summation averaging

Summation averaging is a common, time-domain-based processing technique that is used to reduce the random (uncorrelated) noise component of a signal, improving its signal-to-noise ratio (SNR), while at the same time increasing a digitiser’s measurement resolution and dynamic range. Figure 2 shows an example of how averaging can be used to reveal signal details that are otherwise buried by excessive noise.

In this example, a low-level signal (approximately 3 mV) is completely buried by random noise (top trace). While the source signal is not even visible in the original single-shot acquisition, averaging 10 times shows that there is actually a signal with 5 peaks (middle trace). Averaging 1000 times improves the signal quality even further, revealing the real shape of the signal, complete with secondary maximum and minimum peaks (lower trace). Ideally, if the signal and noise are uncorrelated, i.e., the noise is random while the signal is repetitive, then the summation averaging function can improve the SNR in proportion to the square root of the number of measurements (or averages). For example, averaging a signal 256 times may improve the SNR by as much as 24 dB or increase measurement resolution by around 4 bits. As such, this technique can be used to improve and extend the 12-bit resolution of the M5i series digitizers.

Built-in Threshold Defined Averaging (TDA)

To further enhance the averaging capability and allow the M5i series digitizers to detect an average rare event that might otherwise be lost in excessive background noise, the new firmware option includes a data suppression technique called Threshold Defined Averaging (TDA). TDA allows the user to set a threshold level so that only waveform samples exceeding the level contribute to the accumulated waveform. Baseline noise samples, those that fall below the set level, are then suppressed by being set to zero, or, as an alternative, to a user-defined value. Figure 3 shows a block diagram of the FPGA functionality, and Figure 4 presents a schematic of the TDA process.

As any waveform data that is below the threshold is removed from the averaged waveform, TDA can be a very useful tool for rejecting low-level, correlated (synchronous) noise and other waveform artifacts, such as baseline drift. These are signal anomalies that cannot be removed by a conventional summation averaging process.


The averaging option (M5i.33xx-spavg) is available now for the M5i.33xx series of PCIe high-speed digitizers.

Image Gallery

  • Fig. 2: Averaging is an important technique to extract signals that are lost in random noise. It can also be used to improve measurement resolution, dynamic range and the SNR

    Fig. 2: Averaging is an important technique to extract signals that are lost in random noise. It can also be used to improve measurement resolution, dynamic range and the SNR

  • Fig. 3: The accumulation and TDA functions are both performed on the real-time data coming from the digitizer ADCs by the card’s on-board FPGA

    Fig. 3: The accumulation and TDA functions are both performed on the real-time data coming from the digitizer ADCs by the card’s on-board FPGA

  • Fig. 4: The TDA process suppresses noise by replacing all samples below a set threshold with either a zero or predefined value

    Fig. 4: The TDA process suppresses noise by replacing all samples below a set threshold with either a zero or predefined value

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