Home Miscellaneous Announcements $1.5 million grant to mathematician for pioneering work in GNSS applications

$1.5 million grant to mathematician for pioneering work in GNSS applications

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Mathematician Ingrid Daubechies, whose pioneering work enabled use of wavelet analysis in a variety of fields, including GNSS.
Mathematician Ingrid Daubechies, whose
pioneering work enabled use of wavelet
analysis in a variety of fields,
including GNSS.

US: Prominent mathematician, Ingrid Daubechies, whoโ€™s pioneering work on wavelets is the foundation for various consumer products and GNSS applications, has received a $1.5 million grant from the Simons Foundation. Daubechies is the James B. Duke Professor of Mathematics and Electrical and Computer Engineering at Duke University in Durham, North Carolina.

The Math + X Investigator award provides research funds to professors at American and Canadian universities to encourage novel collaborations between mathematicians and researchers in another field of science or engineering.

โ€œThe mathematical technique of wavelet analysis is being used in several different GNSS applications,โ€ said GPS Worldโ€™s Innovation columnist Richard Langley. In the October 2003 Innovation article โ€œWavelet Multiresolution Analysis,โ€ Langley provides a general introduction to wavelet techniques:

โ€œWavelet analysis is an extension of Fourier analysis, the classical technique that decomposes a signal into its frequency components. However, Fourier analysis cannot determine the exact time at which a particular frequency occurred in the signal.

โ€œWavelet analysis, on the other hand, allows scientists and engineers to study the frequency structure of time-varying signals with unprecedented time resolution.

โ€œIn fact, a signal can be decomposed to obtain a time history of the different frequency bands making up the signal โ€” an approach termed multi-resolution analysis. Wavelet analysis can also compress data for more efficient storage and transmission, replacing the original data values with far fewer wavelet transform coefficients.โ€

Langley explains that to improve GPS accuracy, wavelet analysis is used to โ€œde-noiseโ€ GPS pseudorange measurements, detect and eliminate cycle slips in GPS carrier-phase measurements, and separate biases such as multipath from high-frequency receiver noise.