Precision landing using an adaptive fuzzy multi-sensor data fusion architecture
- Submitting institution
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Kingston University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 12-103-1655
- Type
- D - Journal article
- DOI
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10.1016/j.asoc.2018.04.025
- Title of journal
- Applied Soft Computing
- Article number
- -
- First page
- 149
- Volume
- 69
- Issue
- -
- ISSN
- 1568-4946
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2018
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
-
- Research group(s)
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- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Approaches that estimate accurate positions while unmanned aerial vehicles come towards landing surface are essential because such estimates are useful for autonomous landing, but is still hard to achieve, this paper proposes a new method that solves these challenges. This paper is significant in developing precise positions estimation techniques for unmanned aerial vehicles, showing how adaptive fuzzy data fusion algorithm can be used to overcome the positional inaccuracies associated with the GPS/INS measurements. This work led to generate a research fund from Royal Academy of Engineering.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -