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Signal processing enhances digitizer performance

08 Jun 2015  | Arthur Pini, Greg Tate, Oliver Rovini

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The FFT provides a better understanding of the elements that make up this signal. The primary signal is the 40kHz burst, which is clearly the frequency component with the highest amplitude. There is an 80kHz signal, which is the second harmonic of the 40kHz component. Its amplitude is about 25 dB below the 40kHz fundamental frequency. There are also a lot of low frequency components between 0Hz and 10kHz. The highest components, those near DC, are ambient noise found in the room where the device was used. Averaging may be able to reduce those components, but it may take a much larger number of acquisitions. You should also consider using a filter to pass only the 40kHz component. That leads us to our next signal processing tool.


Filtering
Software used with many digitizers often provides a choice of FIR (finite impulse response) or IIR (infinite impulse response) digital filters in low-pass, band-pass, or high-pass configuration. These filters can be applied to the acquired signal and we can compare the results with the raw or averaged acquisitions. In figure 5, an FIR band pass filter with cut-off frequencies of 30 and 50kHz has been applied to the acquired signal.


Figure 5: Applying FIR band pass filter with cut-off frequencies of 30 to 50kHz to the 40kHz ultrasonic signal. The raw waveform and its FFT are on the left side of the display. The filtered signal and its FFT are on the right side. Note the flatness in the filtered baseline, the result of eliminating the low frequency pickup.


The upper left grid contains the raw waveform. Below that is the FFT of the raw signal which we have seen before. The upper right grid contains the band pass filtered waveform. The FFT of the filtered signal is in the grid on the lower right. Note that the band pass filter has eliminated the low frequency pickup and the 80kHz second harmonic. The time domain view of the filtered signal has a flat baseline. The reflections are clearly discernible, which is the goal of the processing. Again the FFT provides greater insight into the filtering process.


Conclusion
We have investigated the application of several signal processing tools including averaging, FFT, and filtering. Each of these tools has its role in the analysis of acquired signals. These tools are available in digitizer support software. They can also be applied using third-party math or system-integration software.


About the author
Arthur Pini is a technical support specialist and electrical engineer with over 50 years experience in the electronics test and measurement industry. He has supported oscilloscopes, real-time spectrum analysers, frequency synthesisers, digitizers and arbitrary waveform generators for leading manufacturers.

Greg Tate has over thirty years of experience working in Test and Measurement. He specialises in high speed ADC and DAC technology and has extensive knowledge of oscilloscopes, spectrum analysers, arbitrary waveform generators and digitizer products.

Oliver Rovini is an electronic engineer working at Spectrum since 1995. As head of development, he is responsible for hardware and software developments in the area of high speed digitizers and arbitrary waveform generators for PC platforms like PCIe, PXI, Ethernet.


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