A Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

You are here: Homepage > Search

A Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

Evan Dill / Julian Gutierrez / Steve Young / Andrew Moore / Arthur Scholz / Emily Bates / Ken Schmitt / Jonathan Doug

The emergence and development of advanced technologies and vehicle types has created a growing demand for the introduction of new forms of flight operations. These new and increasingly complex operational paradigms such as Advanced and Urban Air Mobility (AAM/UAM) present regulatory authorities and the aviation community with several design and implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is finding methods to integrate these emerging operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. This paper focus on the development and testing of a prognostic service aimed at estimating the quality of Global Navigation Satellite System (GNSS) performance for an autonomous aircraft in complex environments. The intent of this function is to proactively reduce a flight operations risk of exposure to states that may induce poor or unacceptable navigation system performance by factoring in estimates of GNSS quality into pre-flight and/or in-flight route planning. Methodologies for producing quality estimates are specified and results are provided for selected simulation and flight test cases.

Access

Access via TIB

Check availability in my library

Export, share and cite

Document information

Title :

A Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

Contributors:

Evan Dill (author) / Julian Gutierrez (author) / Steve Young (author) / Andrew Moore (author) / Arthur Scholz (author) / Emily Bates (author) / Ken Schmitt (author) / Jonathan Doug (author)

Conference:

ION GNSS+ ; 2021 ; St. Louis, MO, US

Type of media :

Conference paper

Type of material :

No indication

Language :

English

Keywords :

GPS , UAM , GNSS , Air Transportation And Safety