Kalman filter-based reliable GNSS positioning for aircraft navigation

Susmita Bhattacharyya, Dinesh L. Mute, Demoz Gebre-Egziabher

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Reliability (or integrity) is an important performance metric of Global Navigation Satellite Systems (GNSS) for aviation applications. To this end, a reliable Kalman filter (KF)-based GNSS positioning algorithm is developed in this paper for aircraft navigation. More precisely, a novel receiver autonomous integrity monitoring (RAIM) algorithm with a KF is developed in the range domain to ensure reliable aircraft position estimation with GNSS. A major challenge with the range-based approach to KF RAIM is as follows. Its protection level (PL) computation should account for the contributions of all past measurements in an efficient way without growing computational burden over time. In this context, a computationally efficient RAIM algorithm is proposed under the assumption of a single satellite failure. It judiciously forms three simultaneous fault detection tests and appropriately modifies PL calculation. It is shown that the proposed method can address the problem of increasing computational burden over time. Thus, it holds promise for real time implementation on avionics, where processing capacity is generally limited. It also provides faster fault detection and lower PLs than that obtained with a single fault detection test. Performance of the proposed method is compared with two existing RAIM algorithms for an application of an unmanned aerial vehicle.

Original languageEnglish (US)
Title of host publicationAIAA Scitech 2019 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105784
StatePublished - Jan 1 2019
EventAIAA Scitech Forum, 2019 - San Diego, United States
Duration: Jan 7 2019Jan 11 2019

Publication series

NameAIAA Scitech 2019 Forum


ConferenceAIAA Scitech Forum, 2019
Country/TerritoryUnited States
CitySan Diego


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