Next Article in Journal
Current State of Multicast Routing Protocols for Disruption Tolerant Networks: Survey and Open Issues
Previous Article in Journal
A Free Navigation of an AGV to a Non-Static Target with Obstacle Avoidance
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle

Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm Optimization

1
Department of Electronic and Optical Engineering, Space Engineering University, Beijing 101416, China
2
School of Space Information, Space Engineering University, Beijing 101416, China
3
Beijing Space Information Relay and Transmission Technology Center, Beijing 100000, China
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(2), 160; https://doi.org/10.3390/electronics8020160
Received: 14 January 2019 / Revised: 22 January 2019 / Accepted: 28 January 2019 / Published: 1 February 2019
(This article belongs to the Section Circuit and Signal Processing)
  |  
PDF [3402 KB, uploaded 1 February 2019]
  |  

Abstract

Due to the difficulty in deducing the corresponding relationship between results and parameter settings of multiple phases sectionalized modulation (MPSM) jamming, a problem occurs when obtaining the optimal local suppression jamming effect, which limits the practical application of MPSM jamming. The traditional method struggles to meet the requirements by setting fixed parameters or random parameters. Therefore, an optimization algorithm for MPSM jamming based on particle swarm optimization (PSO) is proposed in this study to produce the optimal local suppression jamming effect and determine its corresponding parameter settings. First, we analyzed the relationship between the degree of mismatch and local suppression jamming effect. Then, we set appropriate fitness function and fitness value. Finally, we used PSO to calculate parameter settings of a section situation and phase situation, which minimizes the fitness function and fitness value. The optimization algorithm avoids the tremendous computation of traversing all parameter settings, is stable, the results are repeatable, and the algorithm provides the optimal local suppression jamming effect under different conditions. The simulation experiments demonstrate the feasibility and effectiveness of the optimization algorithm. View Full-Text
Keywords: optimization algorithm; multiple phases sectionalized modulation (MPSM) jamming; particle swarm optimization (PSO); local suppression jamming; fitness function optimization algorithm; multiple phases sectionalized modulation (MPSM) jamming; particle swarm optimization (PSO); local suppression jamming; fitness function
Figures

Figure 1

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 (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Jiang, J.; Wu, Y.; Wang, H.; Lv, Y.; Qiu, L.; Yu, D. Optimization Algorithm for Multiple Phases Sectionalized Modulation Jamming Based on Particle Swarm Optimization. Electronics 2019, 8, 160.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Electronics EISSN 2079-9292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top