Title: Gravity Model Error Considerations for High-Integrity GNSS-aided INS Operations
Author(s): Timothy G. Needham, Michael S. Braasch
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 822 - 832
Cite this article: Needham, Timothy G., Braasch, Michael S., "Gravity Model Error Considerations for High-Integrity GNSS-aided INS Operations," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 822-832.
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Abstract: GNSS-aided inertial systems are used to achieve accurate and reliable position, velocity, and attitude estimates in a wide variety of aerospace applications. When utilized in a safety-critical operation such as civil aviation, every potential error source must be characterized for its potential contribution to hazardously misleading information. The standards-making body, RTCA, facilitates working groups that develop requirements and test criteria in the form of Minimum Operational Performance Standards (MOPS) for airborne equipment. Existing standards address the usage of navigation grade inertial units in long-range operations such as oceanic flight. Currently, RTCA SC-159 WG-2C is developing a new MOPS that, in addition to addressing a wider range of inertial units, will also address coasting during GNSS outages to increase continuity in operations such as non-precision approach. As part of this effort, the effect of gravity mis-modeling on the navigation system during short-term GNSS outages is being investigated from a certification perspective. For certification purposes, the navigation system must be properly stressed/tested using realistic worst case scenarios. Previous gravity modeling work by the authors [1] demonstrated that large gradients in the deflection of the vertical (DOV) can lead to horizontal position errors that are a significant fraction of an RNP 0.3 lane width. This paper extends the previous work in two main areas: a) global analysis of DOV magnitude and gradient; and b) statistical characterization of low, medium and high-order gravity model performance.