Terrain-Relative Navigation With Neuro-Inspired Elevation Encoding

Terrain-relative navigation (TRN) encompasses a wide variety of algorithms that perform localization with respect to the terrain below a flying vehicle. In traditional approaches, measurements of the terrain are matched to a map carried onboard. This work presents a TRN filter with a position measur...

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Veröffentlicht in:IEEE transactions on aerospace and electronic systems Jg. 60; H. 3; S. 3368 - 3378
Hauptverfasser: Michaelson, Kristen A., Wang, Felix, Zanetti, Renato
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.06.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
ADVANCED PROPULSION SYSTEMS
Algorithms
Dictionaries
Encoding
Filtering algorithms
Inertial navigation
kalman filter
Matched filters
Navigation
neuro-inspired
Optimization
Phase measurement
Position measurement
Template matching
Terrain
terrain-relative navigation
terrain-relative navigation (TRN)
ISSN:0018-9251, 1557-9603
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Terrain-relative navigation (TRN) encompasses a wide variety of algorithms that perform localization with respect to the terrain below a flying vehicle. In traditional approaches, measurements of the terrain are matched to a map carried onboard. This work presents a TRN filter with a position measurement inspired by neural activity associated with positioning in nature. The filter is shown to produce accurate position measurements that outperform popular optimization and template matching methods given poor prior knowledge of the position. The proposed method is also better-suited to distributed implementation than optimization-based methods.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
SAND-2024-05437J
NA0003525
USDOE Laboratory Directed Research and Development (LDRD) Program
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2024.3362760