In modern combat， nodes differ significantly from the single-function nodes of the past， evolving towards multi-function integration. To address issues such as the characterization of node function diversity， the dynamic reconfiguration of system models， and realistic simulation of enemy network analysis in current node importance evaluations of combat systems， a dynamic reconfiguration model based on unit attributes for the enemy’s network is proposed. The concept of tactical weight is introduced， and multi-function integration of nodes and edges is achieved through attribute induction and attribute assignment. A method and algorithm for calculating the dynamic reconfiguration of network effectiveness are presented. Taking into account the actual operational context and efficiency， the node attack cost is incorporated， and a node importance evaluation model based on the contribution rate to system network effectiveness is proposed. In simulation experiments， node importance is evaluated using seven different metrics， including node effectiveness index， degree centrality， and betweenness centrality， under various spatiotemporal conditions. The decline in network effectiveness after network strikes is also analyzed. The simulation results demonstrate that the proposed method enables dynamic reconfiguration of the network post-attack， reflecting the network’s strong robustness and confirming the validity of the proposed algorithm.

In view of the autonomous air combat maneuver decision-making problem of unmanned aerial vehicles （UAVs）， a decision-making algorithm based on a path-game hybrid strategy is designed. Firstly， according to the principle that horizontal maneuver and vertical maneuver can be decoupled in the flight control process of UAVs， a decoupled autonomous decision-making mechanism is proposed， which uses path planning to realize horizontal maneuver decision-making and adopts game theory to realize vertical maneuver decision-making. In order to improve the flexibility of the decision-making environment， a dynamic grid environment is designed， which can adaptively adjust the planning range and resolution. The path planning model is designed based on Q-learning （QL） algorithm， and the algorithm is improved by using a double Q-table learning mechanism， which effectively improves the quality of path planning. Based on the Nash equilibrium theory， the vertical maneuver algorithm model is constructed， and the cost calculation function is designed according to different situation environments. Thus， the vertical maneuver decision-making of UAVs is realized. Finally， the simulation of a one-to-one air combat confrontation scenario verifies the effectiveness of the algorithm. Compared with the traditional maneuver decision-making based on three-dimensional planning space， the proposed algorithm can effectively shorten the planning time and improve the planning quality.

Owing to the lack of polarization freedom and the power-driven， the polarization filter cannot meet the demand of setting notch at the interference and setting peak at the target simultaneously. This disadvantage is considered as the fundamental of corrupting filter. The jammer can prevent the radar from obtaining the precise target， interference polarization parameters and stable related interference and noise reference data necessary for the filter by controlling the mode and sequence of polarization of the transmit signal polarization modulation， which in turn prevents the filter notch from aligning with the interference and ensures that sufficient interference signal is received by radar receiver. We analyze the processing characteristics of various polarization filters and predict the filter output performance for various interference backgrounds to obtain the best polarization modulation scheme against each filter. The schemes are verified by simulation experiments.

To impair the accuracy of polarization measurement of radar and hinder the construction of polarization filter， a study of full-polarization interference technology on polarization measurement and a robust， adaptable and operational polarization modulation method are provided. A classic polarization measurement based on the elaborately deduced signal model is described along with its performance analysis. It clarifies that it is the lack of polarization freedom and the power-driven lead to the inherent disadvantage， which is of fundamental importance to interference. Furthermore， it predicts the results imposed by some commonly used interference modes and modulations theoretically， which are verified by simulation experiments. For all above research， the random-polarization interference performs more effective in polarization measurement.