Modern combat is currently undergoing profound changes. Various military strategies and technologies have continuously emerged， such as distributed killing， mosaic warfare and para-suppression engineering. Against this background， this paper focuses on analyzing the characteristics of multi-domain integration in the Russia-Ukraine war， summarizing two major challenges including performance boundary and physical boundary， proposing the development direction of collaborative detection and guidance based on full-domain holographic situational awareness， refining eight key technologies including but not limited to the generic collaborative detection and guidance system architecture， and exploring the ways of implementation. The evolution of detection and guidance technology is promoted to multi-domain joint， cross-domain collaboration and full-domain countermeasure， supporting higher-level information-based warfare in the future.

Multi-agent cooperation and competition has the characteristics of real-time and action continuity， incomplete information， huge search space， multi-complex tasks and time-space inference， etc. It is one of the most challenging problems in the current artificial intelligence field. Aiming at the problem of long training time for large-scale multi-agent reinforcement learning， this paper proposes an Actor-Critic-based cooperative confrontation framework， which uses meta curriculum reinforcement learning method to extract meta-models of basic tasks for small-scale scenarios. We carry out model migration to large-scale scenarios based on the curriculum learning， which continues training based on the meta-models and finally obtains a better collaboration strategy. This paper conducts simulation experiments on the "Star-Craft II" platform. The results show that the multi-agent cooperative confrontation technology based on the meta curriculum reinforcement learning can effectively accelerate the training process， and can achieve a higher win rate within a shorter time compared with the traditional training methods. The training speed is increased by about 40%. This method can effectively support the efficient generation of multi-agent cooperative confrontation strategies.

This paper discusses the differences of the emphasis of human-machine system design between complex information system and Internet products， how to transform functional requirements into design requirements， break through the traditional extensive design， and improve the human-machine coordination and human-machine interaction ability of air defense and anti-missile radar， and puts forward a effectiveness centered design idea and theory based on mission characteristics and timing sequence. This paper presents a new scientific design method for the key links affecting the combat effectiveness of human-machine system， such as human-machine function allocation， intelligent decision support， station division， information architecture of interactive interface and so on. The practice shows that the effectiveness centered design theory and method based on mission characteristics and timing sequence effectively improves the combat effectiveness of weapon equipment human-machine system. This method can effectively guide the human-machine system design of complex information system represented by air defense and anti-missile radar， and can be widely used for all kinds of human-machine systems with strong timeliness.