Solving Multi-Sensor Multi-Target Assignment Problem Based on Compositive Combat Efficiency and QPSO Algorithm

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/).

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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  -