基于改进蜂群算法的多传感器目标分配方法

针对多传感器目标分配中参数多、计算复杂、实时性不强、全局搜索能力不高等问题,在分析其数学模型的基础上,基于改进人工蜂群算法,对目标函数进行优化并确定分配方案.改进后的算法中,跟随蜂采用双向轮盘赌的方式选择引领蜂,并采用萤火虫算法中的自适应步长策略来进行局部搜索,有助于提高算法收敛速度、增强算法的局部搜索能力.仿真结果表明,改进蜂群算法能够有效解决多传感目标分配问题,与基本蜂群算法相比,改进后的算法收敛速度加快、寻优能力得到进一步增强,具有较强的实用价值.

Multi-Sensor Target Allocatioin Method Based on Improved Bee Colony Algorithm

In order to solve the problems of many parameters,complex computation,poor real-time performance and low global search capability of previous algorithms in multi-sensor target allocation,based on the analysis of its mathematical model and the improved artificial bee colony optimization,the objective function is optimized and the allocatioin scheme is determined.In the improved algorithm,following-bee chooses the leading-bee in the way of bidirectional roulette,and the adaptive step strategy of firefly algorithm is used to dynamically adjust the search behavior of following-bee,which helps to improve the convergence speed and enhance the local search ability of the algorithm.Simulation results show that the improved colony algorithm can effectively solve the problem of multi-sensor target allocation.Compared with the basic bee colony algorithm,both the convergence speed and the local search ability are enhanced,and has strong practical value.