基于改进Actor-Critic算法的多传感器交叉提示技术

Multi-sensor cross cueing technique based on improved Actor-Critic algorithm

针对在减少战场资源浪费、平衡战场效费比的同时提高目标探测概率,保证目标的可持续跟踪,提出利用改进Actor-Critic算法的多传感器交叉提示技术进行目标探测。首先,综合传感器探测、能耗、时效等因素搭建基于“交叉提示”传感器的动态管理评估模型;其次,重点分析利用Actor-Critic交叉提示算法的传感器管理决策规则,并且提出了Actor-Critic算法,以根据任务自身需求组建中央评价网络,加大传感器与外部环境的交互。仿真结果表明,改进的算法可以加速网络收益,实现对目标的持续性探测,加强传感器之间的交叉提示功能,提升调度的智能化水平,具有较大的应用价值。

To reduce the waste of battlefield resources,balance the cost-effectiveness ratio of the battlefield,increase the probability of target detection,and to ensure the sustainable tracking of the target,a multi-sensor cross-cueing technique based on improved Actor-Critic algorithm for target detection is proposed in this paper.Firstly,a sensor dynamic management evaluation model based on“cross-cueing”is built by integrating factors such as sensor detection,energy consumption,and timing.Secondly,the paper focuses on analyzing the decision rules of sensor management under the Actor-Critic cross-cueing algorithm.The improvement of the Actor-Critic algorithm is proposed to form a central evaluation network according to the needs of the task itself,and enlarge the interaction between the sensor and the external environment.Simulation result shows that the improved algorithm can accelerate the profit of the alliance,realize the continuous detection of the target,strengthen the cross-cueing function between sensors,and improve the intelligent level of scheduling,which provides great application value.