Multi-Platform Fire Control Strike Track Planning Method Based On Deep Enhance Learning

The modern war has been transforming from center-based to cyber-based. The cyber war is an information network system, which is composed by detective system, communication system, command and control system, and weapon system. In such system, commander can see all battlefield situations, change combat information, design and implement combat plan. Cloud-based platform would be the development trend of next generation avionics system in cyber combat. In order to improve system combat efficiency, in this paper, we propose a multi-platform fire control strike track planning method based on deep enhance learning. It uses deep enhance learning model to generate higher hit rate fire control strike track. The experiment shows our proposed method is more efficient.