Design of cloud-edge-end collaborative intelligent simulation platform for flight simulation training

In response to the demands of large-scale cross-regional networked tactical confrontation flight simulation training, an intelligent simulation platform architecture based on cloud-edge-end collaboration has been designed. The architecture supported by big data and centered around intelligent large models, intelligent agents and real-time simulation models, enables multi-modal operation integrating peacetime and training running modes through cross-regional cloud-edge-end resource integration, dynamic reuse, collaborative simulation and virtual-real fusion. Based on an analysis of the functional requirements of this intelligent simulation platform, the study focuses on designing its hierarchical architecture, network structure, and synchronized simulation strategies. It investigates critical aspects including cloud-edge-end simulation task allocation, operational modes, and application scenarios. Three key technical challenges are explored including integration of cloud-based XR and AI technologies, cloud-based convergence of big data, large models and real-time simulation, and real-time interactive cloud-edge-end collaborative simulation. This work provides a reference model for constructing a new-generation intelligent simulation platform that supports all-scenario, full-system, multi-element training, thereby advancing intelligent transformation in flight simulation training domains.