基于改进D-S证据理论的多源空战信息博弈融合方法

多传感器系统与单传感器系统相比能够更大限度地获取被探测目标的信息量，但在空战中无人机传感器探测得到的数据在一定程度上具有欺骗性，利用博弈融合技术对多传感器数据进行融合，能够获得更加符合空战实际需要的信息。为此，研究了一种基于改进D-S(Dempster-Shafer)证据理论的多源空战信息博弈融合技术，在信息融合前采用Jousselme距离进行预处理，并利用费雪信息进行冲突数据博弈，所得策略集使空战数据更加可靠。在此基础上，根据邓熵方法对基于D-S证据理论的融合方法进行改进，与传统D-S证据理论方法相比，融合数据符合空战实际。最后对存在冲突的多源空战信息进行博弈融合仿真，仿真结果验证了该方法的可行性与优势。

Air Combat Information Game Fusion Method Based on Improved D-S Evidence Theory

Compared with a single-sensor system, a multi-sensor system can obtain the information of the detected target to a great extent. However, data detected by unmanned aerial vehicle sensors in air combat is deceptive to a certain extent. Using the game fusion technology to fuse multi-sensor data can obtain information in line with the actual needs of air combat. A multi-source air combat information game fusion technology is studied based on the improved Dempster-Shafer (D-S) evidence theory. Before information fusion, Jousselme distance is employed for preprocessing, and Fisher information is used for a conflict data game to obtain a strategy set to make air combat data reliable. On this basis, the fusion method based on D-S evidence theory is improved according to the Deng entropy method. Compared with the traditional D-S evidence theory method, the fusion data conform to those in actual air combat. Finally, a game fusion simulation is performed on conflicting multi-source air combat information. The simulation results verify the feasibility and advantages of the developed method.