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Scheduling based on the hybrid genetic particle swarm algorithm for the phased array radar

ZHANG Haowei1, XIE Junwei1, ZHANG Zhaojian1, ZONG Binfeng2, SHENG Chuan1#br#   

  1. (1. Air and Missile Defense College, Air Force Engineering University, Xi’an 710051, China;
    2. Unit 94710 of the PLA, Wuxi 214000, China)

  • Online:2017-08-28 Published:2010-01-03

Abstract:

A hybrid algorithm, which integrates the particle swarm algorithm, the genetic algorithm and the heuristic interleaving algorithm, is proposed to solve the task scheduling problem in the phased array radar. In the proposed algorithm, the chaos theory is adopted to modulate the velocity parameters in the particle swarm algorithm, the diminishing dynamic inertia weight is designed and the crossover operation and the mutation operation in the genetic algorithm are introduced to enhance the efficiency and the global exploration ability of the algorithm. In addition, the heuristic interleaving algorithm is put forward under the frame of the intelligence algorithm. It can further utilize the time resource between the transmitting duration and receiving duration in radar tasks. The simulation results demonstrate that the proposed algorithm possesses the merits of the quicker convergence and better results compared with the genetic algorithm. In addition, the proposed algorithm improves the successfully scheduling ratio by 42%, time utilization ratio by 40%, high value ratio by 33%, and decreases the average time shift ratio by 73% compared with the heuristic algorithm.

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