Governed by: Ministry of Industry and Information Technology of the People's Republic of China
Sponsored by: Northwestern Polytechnical University  Chinese Society Aeronautics and Astronautics
Address: Aviation Building,Youyi Campus, Northwestern Polytechnical University
Improved Grey Wolf Optimization for Electronic Jamming Airspace Layout
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Affiliation:

air traffic control and navigation collage,air traffic control and navigation collage,air traffic control and navigation collage

Clc Number:

V355.1

Fund Project:

national air traffic control committee research project: research on the key technology of airborne of unmanned aerial vehicles

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    Abstract:

    Aiming at optimal airspace layout of electronic jamming during air fighter’s penetration operation, the range of radar detection under electronic jamming, route safety interval, and effective jamming time under electronic interference were described. In order to achieve the safety penetration of the penetration fighters, to ensure the safety of the jammer itself, and to achieve the purpose of efficient use of airspace resources, the optimal airspace layout model of the electronic jamming machine was established, and Improved Grey Wolf Optimization (IGWO) was used to find the optimal airspace reference point. In order to avoid falling into the local optimum, the linear adjustment parameter in original grey wolf optimization was changed to a non-linear one, and the memory function in the particle swarm optimization was added. The simulation results showed that Improved Grey Wolf Optimization (IGWO) was superior to the original grey wolf optimization algorithm and particle swarm optimization, could quickly find the optimal airspace reference point to complete a specific penetration task, and then designed the optimal airspace of the electronic jamming aircrafts. It also proved that the model was scientific and effective.

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WANG Qing-Hao, YAO Deng-kai, ZHAO Gu-hao. Improved Grey Wolf Optimization for Electronic Jamming Airspace Layout[J]. Advances in Aeronautical Science and Engineering,2018,9(3):326-333

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History
  • Received:December 05,2017
  • Revised:February 28,2018
  • Adopted:March 09,2018
  • Online: July 16,2018
  • Published: