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     Research Journal of Applied Sciences, Engineering and Technology


Optimal Deployment Problems of Radar Network

Shang Gao
School of Computer Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212003, China
Research Journal of Applied Sciences, Engineering and Technology  2013  10:1879-1883
http://dx.doi.org/10.19026/rjaset.6.3919  |  © The Author(s) 2013
Received: November 20, 2012  |  Accepted: January 14, 2013  |  Published: July 20, 2013

Abstract

The deployment problems of the radar sets are important in the air defense of the military. The target detection joint probability of several radar sets is studied. The optimum deployment models of circle, line and sector have been built up. The area of space, which is determined by the detection joint probability is more than 0.9, is got by the use of Monte Carlo method. The optimum deployments problems of the circle deployment, line deployment and sector deployment can be solved by entire enumerate method, golden section method and coordinate alternation method. On condition that the number of radar is less in the twice-ines deployment model it can be solved by combine entire enumerate method with coordinate alternation method. Contrarily, it can be solved by combining genetic algorithm with coordinate alternation method.

Keywords:

Coordinate alternation method, genetic algorithm, golden section method, Monte Carlo method, target detection probability,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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