基于多agent协同跟踪调度技术研究

Research on scheduling technology of cooperative tracking based on multi-agent

为了减少时效性要求较高的动态目标跟踪的调度时间,提出了一种基于多agent的自适应协同跟踪平台选择算法。首先,提出agent模型的应用;然后,以最小化调度时间和跟踪误差为目标建立适应度函数,采用合同网结合二值粒子群优化的方法,选出针对特定目标的最佳跟踪平台组合。仿真结果表明,与现有的几种算法相比,该算法有效地减少了调度时间,提高了跟踪精度,适用于实时性高的高速运动目标跟踪。

Aimed to reduce the time of the tracking system consumes when schedules tracking platforms for the dynamic highly real-time targets, this paper proposed a collaborative tracking algorithm selecting tracking platforms adaptively based on agents. Firstly, it used agents model to represent the platforms. Then, it aimed to minimize scheduling time and tracking er- ror, and used a contract net protocol combined with binary particle swarm optimization algorithm to select the best tracking platforms. Simulation results show that the proposed algorithm can effectively reduce the scheduling time and improve the tracking accuracy compared with the existing algorithms, so it is suitable for tracking high speed moving target in real-time.