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Mathematical Problems in Engineering
Volume 2017, Article ID 9843735, 12 pages
https://doi.org/10.1155/2017/9843735
Research Article

Research on Multiaircraft Cooperative Suppression Interference Array Based on an Improved Multiobjective Particle Swarm Optimization Algorithm

1Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xian 710038, China
2Tianjin University, Tianjin 300072, China

Correspondence should be addressed to Huan Zhang; nc.ude.ujt@4111ycs

Received 26 October 2016; Revised 11 January 2017; Accepted 17 January 2017; Published 5 March 2017

Academic Editor: Thomas Hanne

Copyright © 2017 Huan Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

For the problem of multiaircraft cooperative suppression interference array (MACSIA) against the enemy air defense radar network in electronic warfare mission planning, firstly, the concept of route planning security zone is proposed and the solution to get the minimum width of security zone based on mathematical morphology is put forward. Secondly, the minimum width of security zone and the sum of the distance between each jamming aircraft and the center of radar network are regarded as objective function, and the multiobjective optimization model of MACSIA is built, and then an improved multiobjective particle swarm optimization algorithm is used to solve the model. The decomposition mechanism is adopted and the proportional distribution is used to maintain diversity of the new found nondominated solutions. Finally, the Pareto optimal solutions are analyzed by simulation, and the optimal MACSIA schemes of each jamming aircraft suppression against the enemy air defense radar network are obtained and verify that the built multiobjective optimization model is corrected. It also shows that the improved multiobjective particle swarm optimization algorithm for solving the problem of MACSIA is feasible and effective.