An Evaluation of Fixed-Wing Unmanned Aerial Vehicle Trends and Correlations with Respect to NATO Classification, Region, EIS Date and Operational Specifications

The current study provides a thorough analysis and evaluation of fixed-wing UAV correlations with respect to NATO classification, region of production, entry-into-service (EIS) date and other operational specifications. A set of 202 existing fixed-wing platforms is used to populate an in-house datab...

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Bibliographic Details
Main Authors: Dimitrios Mitridis, Stavros Kapsalis, Dimitrios Terzis, Pericles Panagiotou
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Aerospace
Subjects:
Online Access:https://www.mdpi.com/2226-4310/10/4/382
Description
Summary:The current study provides a thorough analysis and evaluation of fixed-wing UAV correlations with respect to NATO classification, region of production, entry-into-service (EIS) date and other operational specifications. A set of 202 existing fixed-wing platforms is used to populate an in-house database. A screening of the corresponding data is conducted using a correlations matrix, and a statistical analysis of the key UAV design parameters is, in turn, performed. The results are presented using a wide variety of charts and statistical coefficients, to provide as much information as possible for future UAV design and performance assessment studies. Correlations for each mission type are provided, followed by a detailed evaluation of the key design parameters and design ratios (wingspan, gross takeoff weight, empty weight, payload weight, endurance, and operational speeds) with respect to NATO classification and region of origin. These key parameters are then plotted as a function of EIS date for every NATO category to identify any underlying trends and, finally, the platforms are classified in regard to some qualitative attributes, such as mission type and low observability. The results suggest that the trendlines extracted for each category significantly deviate from the generic trends. Therefore, omitting the classification in terms of region, size and weight can lead to misleading outcomes and should be avoided. Another conclusion lies in the fact that, apart from the average trendline, the design engineers should also have an indication of the data variance, due to the high dispersion observed in the datasets of several design parameters.
ISSN:2226-4310