任务性能约束下传感器协同辐射控制策略

传感器协同是作战飞机实现任务性能与射频(radio frequency,RF)隐身性能平衡的重要技术手段。针对传统引导搜索方法难以解决数据链的多拍信息引导搜索问题,采用概率方法,建立多拍连续引导信息与累积发现概率、累积被截获概率之间的关系。针对基于协方差的线性规划协同跟踪方法的单步决策问题,开展基于跟踪精度与被跟踪定位精度的多步联合优化。引入马尔可夫决策过程对机载传感器协同搜索、协同跟踪的典型空战动态过程进行建模,实现任务性能约束下的雷达RF隐身性能优化。通过典型空战场景的仿真验证,表明所提出的优化控制策略相比于经验控制策略能够减少雷达辐射时间43%以上。

Research on sensor cooperative radiation control strategy under task performance constraints

Sensor coordination is an important technical means for combat aircraft to achieve mission performance and RF stealth performance balance. Aiming at the problem that the traditional guided search method is difficult to solve the multi-shot information guided search problem of the data link, the probabilistic method is used to establish the relationship between the multi-shot continuous guidance information and the cumulative discovery probability and the cumulative intercept probability. A multi-step joint optimization based on tracking accuracy and tracked positioning accuracy is proposed for the single step decision problem of covariance based linear programming collaborative tracking method. The Markov decision process is introduced to model the typical air combat dynamic process of airborne sensor collaborative search and cooperative tracking, and the radar RF stealth performance optimization under task performance constraints is realized. The simulation results of typical air combat scenarios show that the proposed optimal control strategy can reduce the radar radiation time by more than 43% compared with the empirical control strategy.