Bounding Temporally Correlated Measurement Noise with an Application to GNSS Integrity

Juan Blanch, Eric Phelts, Kaz Gunning, Todd Walter, Lance de Groot, Laura Norman

Abstract:	In GNSS techniques like Precise Point Positioning (PPP), many of the errors affecting the position solution are modelled and estimated over time. In order to use PPP or related techniques for applications that require integrity, we need models of the errors that will lead to upper bounds of the estimated error covariance. In this work, we use the properties of the power spectral density to develop error models that bound autoregressive models with uncertain parameters. As an example, we show how this approach can be applied to the determination of a first order model that bounds the clock and ephemeris errors of GPS for multiple satellites.
Published in:	Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2020) September 21 - 25, 2020
Pages:	27 - 38
Cite this article:	Blanch, Juan, Phelts, Eric, Gunning, Kaz, Walter, Todd, de Groot, Lance, Norman, Laura, "Bounding Temporally Correlated Measurement Noise with an Application to GNSS Integrity," Proceedings of the 33rd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2020), September 2020, pp. 27-38. https://doi.org/10.33012/2020.17549
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