Abstract
GNSS denied IMU correction is a practical challenge in aerospace vehicle navigation. In the context of several vehicles flying in formation, navigation accuracy can be enhanced by communication between the vehicles. In this paper, a collaborative navigation strategy is presented to deal with coarse and ambiguous measurements. An absolute navigation filter provides a first estimate of the navigation solution, while a relative observer rebuilds the neighbors relative states from embedded seekers. A high-level Master Filter fuses information provided by those two low-level filters to enhance the navigation solution. Absolute navigation measurements are terrain elevation data correlated with a Digital Elevation Model map. Since they are highly ambiguous and nonlinear, they are processed by a Box Regularized Particle Filter. The relative measurements under consideration suffer a high level of uncertainty, especially on the relative distance between vehicles. By fusing all uncertain data, a complete and accurate navigation solution is obtained. Numerical results are presented and show an enhancement in navigation performance by exchanging information, in terms of RMS estimation error (63% more accurate in position), estimation confidence (78% more precise in position), and computational load (requires 83% less operations).
Original language | English |
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Title of host publication | 2017 IEEE 56th Annual Conference on Decision and Control (CDC) |
Publisher | IEEE |
Pages | 375-380 |
Number of pages | 6 |
ISBN (Electronic) | 978-1-5090-2873-3, 978-1-5090-2872-6 |
ISBN (Print) | 978-1-5090-2874-0 |
DOIs | |
Publication status | Published - 23 Jan 2018 |
Event | Annual Conference on Decision and Control - Melbourne, Australia Duration: 12 Dec 2017 → 15 Dec 2017 Conference number: 56 |
Conference
Conference | Annual Conference on Decision and Control |
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Abbreviated title | CDC |
Country/Territory | Australia |
City | Melbourne |
Period | 12/12/17 → 15/12/17 |
Bibliographical note
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Keywords
- Navigation
- Acceleration
- Particle measurements
- Atmospheric measurements
- Measurement uncertainty
- Computer architecture
- Uncertainty