Multi-Frame Multi-Sensor Multi-Target Task Allocation Method Based on Improved Wolf Colony Algorithm
Feng Ping Yang, Pengxiang Wang, Yizhai Zhang · 2018
With the increasing number of targets, limited sensor resources cannot meet the requirements of reasonable management. Therefore, how to solve the problem effectively has been widely concerned by scholars. The traditional allocation method only considers single frame allocation, and ignores the relationship between the results of consecutive several frame. Thinking about the sequentiality for continuous time frames, a multi-frame multi-sensor multi-target task allocation method based on improved Wolf Colony Algorithm (WCA) is proposed. In the paper, the influence of the allocation results of the previous frames on at current frame is considered. The threat degree of the next frame of the target which has not been assigned sensor monitoring for several consecutive frames is updated based on the pervious allocation results in multi frames. The multi-sensor multi-target task allocation problem is modeled as a constrained optimization problem, which is solved by the Improved WCA. Simulation results show that the result of allocation of sensor resources is more reasonable, with increase slightly of the allocation time cost, compared with Improved WCA without the method.