In view of the problem of electronic and firepower integrated multilayer air defense forces interception capability evaluation， regarding the ground-to-air radar jamming system， medium-range air defense missile， short-range air defense missile and antiaircraft weapon as multilayer multi-channel system composed of 4 layers of defense， the interception capability evaluation model of electronic and firepower integrated multi-layer and multi-channel air defense system based on finite waiting queuing system and loss queuing system is established. The example analysis shows that the method can provide a scientific assessment method to the effectiveness of electronic and firepower integrated multilayer air defense system and it can provide reference and basis for optimizing the deployment plan of air defense forces.

Driven by the increasing intelligence of potential threats and the continuous progress of current intelligent technology， the air and space defense combat system of systems （SoS） is not a linear superposition and mechanical stacking of equipment and technology but a comprehensive intelligent agent that organically integrates， dynamically adapts， and continuously evolves various combat elements. On the basis of analyzing the characteristics of intelligent air and space defense combat SoS， this paper innovated the intelligent design paradigm and concept， proposed a SoS architecture design method based on intelligent agent networks， and explored the key technologies of intelligent empowerment architecture design from three aspects： force nodes， force relationships， and adaptive mechanisms. This method provides an intelligent method reference for the top-level design of air and space defense forces， which helps to improve the intelligence and networking level of the construction and application of air and space defense combat SoS.

In view of the complex low-altitude airspace environment and the fact that unmanned aerial vehicle（UAV） operation risks cannot be quantified， a low-altitude UAV operation risk assessment method considering the uncertainty in the operation process is proposed. According to the force model during the descent of the UAV， the area affected by the sudden failure of the UAV is deduced. Considering the uncertainty in the operation of the UAV， the Monte-Carlo method is used to determine the UAV’s fall point distribution， the impact area of the fall is calculated， and the system risk value is obtained. Through case analysis， the validity and rationality of the proposed risk assessment method are verified， which can provide real-time safety assessment for low-altitude UAV air traffic management， and guarantee the UAV operates safely in the low-altitude airspace.