Abstract
The collaborative combat of manned/unmanned aerial vehicles (MAVs/UAVs) is a popular topic in combat application research. It maximizes the autonomous combat capability of UAVs and the control capability of MAVs. Furthermore, it improves the comprehensive combat effectiveness. The quantitative description of intercommunication in different aircrafts along with the evaluation of the collaborative combat capability is an emphasis in military research. This paper analyzes the collaborative combat process. Node and edge models are established in the MAV/UAV collaborative network. The intercommunication and combat behaviors among combat entities are analyzed. Based on the information entropy, the effect of capability uncertainties on the collaborative combat is described quantitatively. An evaluation method of the MAV/UAV collaborative combat capability is proposed. Finally, an example is given to demonstrate the proposed model and evaluation method that prove its feasibility and effectiveness.
Highlights
With the development of aviation technology and the increasing military demands, the research and development (R&D) of unmanned aerial vehicles (UAVs) has gradually developed trends of generalization and serialization [1]
Step 5: Obtain the manned/unmanned aerial vehicle (MAV/UAV) collaborative combat capability by calculating the combat capabilities of the operation loops aimed at all the targets
According to the technical indexes of the different nodes in the MAV/UAV collaborative combat network, the capability and information entropy of each edge can be calculated when combined with the analysis of the relationships among the nodes
Summary
With the development of aviation technology and the increasing military demands, the research and development (R&D) of unmanned aerial vehicles (UAVs) has gradually developed trends of generalization and serialization [1]. With the deepening knowledge of equipment systems, the Department of Defense Architecture Framework (Do DAF) [5, 6], proposed by the US Army, has been unable to reflect the complexity, connectivity, and networking features of the combat process. To remedy this limitation, experts have explored new methods to make the model more reasonable. Tolk et al [11] improved the information age model established by Cares but did not consider the impact of node performance on combat effectiveness [12, 13]. The research provides a quantitative decision basis for military R&D and the procurement of
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