Solving Multi-Sensor Multi-Target Assignment Problem Based on Compositive Combat Efficiency and QPSO Algorithm
Authors
Gongguo Xu, Xiusheng Duan, Wenhua Hu, Hailong Zhang
Corresponding Author
Gongguo Xu
Available Online June 2016.
- DOI
- 10.2991/mmebc-16.2016.418How to use a DOI?
- Keywords
- Multi-Sensor Multi-Target Assignment; Quantum Particle Swarm Optimization; Air Defense System
- Abstract
Aiming at the multi-sensor multi-target assignment (MSMTA) problem under complex air defense combat environment, a new MSMTA model is proposed with the compositive combat efficiency of the identification, tracking and positioning stage. And then, the quantum particle swarm optimization (QPSQ) algorithm is imported in order to solve the MSMTA problem. Finally, the experiments show that the new MSMTA model is effective and compare the performances between the QPSO and particle swarm optimization (PSO) algorithms.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Gongguo Xu AU - Xiusheng Duan AU - Wenhua Hu AU - Hailong Zhang PY - 2016/06 DA - 2016/06 TI - Solving Multi-Sensor Multi-Target Assignment Problem Based on Compositive Combat Efficiency and QPSO Algorithm BT - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer PB - Atlantis Press SP - 2089 EP - 2093 SN - 2352-5401 UR - https://doi.org/10.2991/mmebc-16.2016.418 DO - 10.2991/mmebc-16.2016.418 ID - Xu2016/06 ER -