What question did this study set out to answer?

To review and analyze sensor fusion methodologies, algorithmic computational complexity, and localization strategies for unmanned aerial vehicles operating in GNSS-denied outdoor environments.

April 6, 2025Satellite NavigationOpen Access

Gnss-denied unmanned aerial vehicle navigation: analyzing computational complexity, sensor fusion, and localization methodologies

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Authors

IJImen JarrayaPrince Sultan University AAAbdulrahman Al-BatatiPrince Sultan University MKMuhammad Bilal KadriPrince Sultan University

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Implication

Review identifies vision-based sensor fusion as optimal for GNSS-denied localization in unmanned aerial vehicles, highlighting the need for hybrid multi-sensor frameworks.

Key Points

To review and analyze sensor fusion methodologies, algorithmic computational complexity, and localization strategies for unmanned aerial vehicles operating in GNSS-denied outdoor environments.
Synthesized existing localization frameworks, sensory devices, and processing algorithms designed for outdoor unmanned aerial vehicles without satellite access.
Formulated a classification taxonomy distinguishing navigation techniques into absolute localization and relative localization systems.
Classified GNSS-denied navigation into absolute and relative localization domains, defining the operational constraints and situational trade-offs of each category.
Identified vision-based localization as the most effective standalone sensing methodology for navigating satellite-compromised environments.
Determined that single-sensor architectures cannot reliably fulfill outdoor navigation requirements, necessitating multi-sensor hybrid fusion algorithms.

Cite This Study

Jarraya et al. (2025) studied this question.

synapsesocial.com/papers/6a1bd66f1567d2fc4d5f1c7f https://doi.org/10.1186/s43020-025-00162-z

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Implication

Review identifies vision-based sensor fusion as optimal for GNSS-denied localization in unmanned aerial vehicles, highlighting the need for hybrid multi-sensor frameworks.

Gnss-denied unmanned aerial vehicle navigation: analyzing computational complexity, sensor fusion, and localization methodologies

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Implication

Key Points

Cite This Study

Gnss-denied unmanned aerial vehicle navigation: analyzing computational complexity, sensor fusion, and localization methodologies

Discussion

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Implication

Key Points

Cite This Study

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