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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| Published in: | IEEE transactions on aerospace and electronic systems Vol. 60; no. 3; pp. 3368 - 3378 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
IEEE
01.06.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 0018-9251, 1557-9603 |
| Online Access: | Get full text |
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| Summary: | 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. |
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| Bibliography: | 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 |