Directional warhead technology is a new killing technology that uses target miss direction information to change the blasting direction through the change of missile body or the logic control of warhead initiation to achieve the maximum damage effect. It is also one of the key promising technologies for the future new generation of air-defense missiles to achieve capability leaping. The overall design problems of the aimed killing air-defense missile equipped with a directional warhead are studied. Firstly， a prediction method of miss information that compensates the missile acceleration for aimed killing air-defense missiles is proposed. The demand for acquiring miss information in advance is met. Secondly， the distributing regularity of the predicted impacting point and the formation mechanism of fuzzy prediction are studied， which provides theoretical support for solving the fuzzy problem. Thirdly， the aiming accuracy improvement methods for small miss distance encounter cases are studied. Finally， the simulations taking a certain type of aimed killing air-defense missile as examples are conducted.

Unmanned aerial vehicle swarm （UAVS） operation is a new operation mode in the future war. The resilience reconstruction capability of the UAVS network is a key index to evaluate the combat effectiveness of the UAVS system. The resilience reconstruction mechanism of the UAVS network is analyzed. A community network model of UAVS is designed to improve network connectivity. Since the network performance of UAVS is sharply degraded under malicious attack， the minimum threshold of information network interaction capability is proposed， and the resilience evaluation method of swarm network performance at the failure stage is optimized. Finally， the average shortest path， information interaction capability， network clustering coefficient， and other parameters of the network under different scales are compared by simulation modeling. The swarm network is reconstructed under the condition of multi-type and multi-scale damage， and the impact on network resilience is evaluated. The experimental results show that the proposed model has higher resilience. The research results can improve the ability of UAVS to cope with complex disturbances and provide theoretical guidance for the multi-task planning of UAVS.

In modern wars， it is difficult for traditional air defense systems to effectively and economically counter unmanned aerial vehicle （UAV） swarm， and ground-based laser systems have become an important means of UAV swarm defense under the key area defense scenarios. Research on the deployment of laser systems will help give full play to their combat capability. Based on the power density concept， the damage model of ground-based laser systems to the UAV target flying at a uniform speed in a straight line is derived. A fitness function is designed to evaluate the advantages and disadvantages of the deployment scheme. Additionally， the particle swarm optimization （PSO） algorithm is adopted to provide the optimal deployment scheme under different specifications and quantities of deployable laser systems， and under different possible attack directions， heights， and speeds of UAVs. Comparison with the scheme of deploying all the laser systems in the center of the key area and of deploying these systems randomly verifies the correctness of the proposed scheme.