Intent-based dynamic model estimation for airborne GNSS positioning

Li Fu, Jun Zhang, Rui Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the development of satellite technologies, global navigation satellite systems (GNSS) are playing a more and more important role in aviation applications. Normally, a GNSS receiver calculates the position solutions under the framework of the Kalman filtering (KF). However, it may bring a low-accuracy positioning result as the dynamic model of the KF can hardly reflect the motion behaviors realistically. The purpose of this paper is to develop a new airborne GNSS positioning algorithm, whose dynamics is estimated based on the flight intent information. First, the flight intent is defined as an objective to fly along the desired path to guarantee the flight safety and efficiency. Then, by modeling the spaced-based guard function and the correction action, an intent-based dynamic model is presented to describe the real flight. Finally, an efficient interacting multiple model (e-IMM) method is applied for dynamic model estimation and navigation positioning. The experimental results demonstrate the effectiveness of our proposed algorithm over the existing methods in dynamics estimation and positioning accuracy.

Original languageEnglish
Title of host publication27th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2014
PublisherInstitute of Navigation
Pages879-887
Number of pages9
ISBN (Electronic)9781634399913
Publication statusPublished - 2014
Externally publishedYes
Event27th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2014 - Tampa, United States
Duration: 8 Sept 201412 Sept 2014

Publication series

Name27th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2014
Volume1

Conference

Conference27th International Technical Meeting of the Satellite Division of the Institute of Navigation, ION GNSS 2014
Country/TerritoryUnited States
CityTampa
Period8/09/1412/09/14

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