Reduce storage requirements for Electromagnetic Environment (EME) spectrum data
© Ploughshare Innovations Ltd 2024. Registered in England and Wales No. 04401901
With Continuous Wavelet Transform (CWT), users are able to analyse signals in communication technologies that people use every day, which provides insights into how improvements can be made in efficiency, performance, and more – but there are limitations. A new innovation has been created which overcomes the key issues users currently face – allowing the analysis of both time and frequency domains at the same time.
CWT is a mathematical transform technique which is used to investigate the varying time-frequency characteristics of non-stationary waveforms (the frequency of the waveform is adjusting continuously – for example, in communication channels where there is not just a constant frequency).
This currently provides:
These resolution limits work well for many non-stationary (real) waveforms, which have slowly changing vibrations punctured with momentary variations in frequency. However, there are occasions when users may wish to obtain both good frequency resolution and good time resolution at high or low frequencies, which is where the current technique falls short.
This issue can now be overcome through a new mathematical device – achieving both good frequency resolution and time resolution at the same time in both low and high frequencies. This is achieved by pre-processing the (complex) input waveform with CWT resolution inversion (which means completing CWT on both the original signal and an inverted signal).
This significant improvement in signal analysis ability can allow users an easier way to analyse multiple aspects of signals at the same time, regardless of the frequency level, and pinpoint where improvements can be made.
The mathematical method originated from the radio frequency (RF) electronics industry but can be used in almost any industry.
Uses can include signal filtering and analysis, signal compression, transient detection, image processing or compression (possible e.g. laser printers), damping ratio of oscillating signals, seismic signal processing, partial differential equation solving, filter design, pattern recognition, and acoustic processing.
This innovation could also potentially be used by medical professionals to analyse heart rates in patients.
If you would like to discuss this technology or collaboration opportunities with our team, please get in touch below.
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