多传感器交叉提示技术在目标检测中的应用

Application of multi-sensor cross cueingtechnology to target detecting

针对多传感器交叉提示技术在目标检测中的应用问题展开研究,将交叉提示分为"信息提示"和"任务提示"2种类型,建立以"信息提示"为基础的传感器效能模型以及目标检测概率计算模型、传感器资源能耗计算模型,为求解"任务提示"中的传感器——目标分配方案问题,设计基于博弈论的多传感器交叉提示分布式算法,该算法中,传感器博弈策略的更新以最优反应动态为原则,随后从理论上分析了算法的收敛性和有效性.仿真实验表明,与合同网算法、拍卖算法等分布式算法相比,该算法具有较快的计算速度,与粒子群算法等集中式算法相比,该算法具有较好的求解质量,充分说明了该算法的有效性、先进性.

The use of multi-sensor crossing cueing technology in target detecting is studied. The types of cross cueing is classfied as information cueing and target cueing. Firstly, efficiency model of sensors basing on information cueing, the target detection probability model, and the sensor energy consumption model are built. Secondly, in order to calculate the sensor-target allocation scheme, the distributed algorithm of multi-sensor cross cueing basing on the game theory is designed;and then in the algorithm, sensors change their game strategy is based on the principle of optimal reaction dynamics. What’s more, the convergence and effectiveness of the algorithm are analyzed theoretically. Finally, the simulation indicates that in comparison of the contract net protocol algorithm and the auction algorithm which are distributed algorithms, the computing speed of the algorithm in this paper is higher, and in comparison of the particle swarm algorithm which is a centralized algorithm, the result of the algorithm in this paper is better, so as to show that the algorithm in this paper is effective and advanced.