skip to main content
10.1145/3446999.3447633acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicitConference Proceedingsconference-collections
research-article

A Stackelberg Game-based Power Allocation Strategy for Multistatic Radar System in the presence of Multiple Jammers

Published: 09 April 2021 Publication History

Abstract

This paper investigates the problem of power allocation for multistatic radar system in the presence of multiple jammers. The primary goal of each radar is to minimize its transmit power under a specified detection threshold, while the jammers aim to maximize the interference to the radars by estimating the power emitted by the radars. The conflict between the radars and the jammers is modeled as a Stackelberg game, in which the radar system is the leader and the jammers act as the followers. Then, the existence and uniqueness of Stackelberg Nash Equilibrium (SNE) are proved by giving the analytical expression of SNE strategies of the jammers. Furthermore, an iterative power allocation algorithm that achieves the SNE is presented. Finally, simulation results verify the convergence and effectiveness of the proposed scheme.

References

[1]
Skolnik, Merrill Ivan. 1980. Introduction to radar systems (Vol. 3). McGraw-hill.
[2]
A. Deligiannis, G. Rossetti, A. Panoui, S. Lambotharan and J. A. Chambers. 2016. Power allocation game between a radar network and multiple jammers. 2016 IEEE Radar Conference (RadarConf), Philadelphia, PA, 1-5. https://doi.org/ 10.1109/RADAR.2016.7485077
[3]
C. Shi, F. Wang, S. Salous and J. Zhou. 2019. A Robust Stackelberg Game-Based Power Allocation Scheme for Spectral Coexisting Multistatic Radar and Communication Systems. 2019 IEEE Radar Conference (RadarConf), Boston, MA, USA, 1-5. https://doi.org/10.1109/RADAR.2019.8835607
[4]
B. He and H. Su. 2019. Joint Power Allocation and Beamforming between a Multistatic Radar and Jammer Based on Game Theory. 2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN), Chongqing, China, 337-341. https://doi.org/10.1109/ICCSN.2019.8905330
[5]
C. Shi, F. Wang, M. Sellathurai and J. Zhou. 2018. Non-Cooperative Game Theoretic Power Allocation Strategy for Distributed Multiple-Radar Architecture in a Spectrum Sharing Environment. J. IEEE Access 6, (2018), 17787-17800. https://doi.org/ 10.1109/ACCESS.2018.2817625
[6]
G. Yang, B. Li, X. Tan and X. Wang. 2014. Adaptive power control algorithm in cognitive radio based on game theory. J. IET Communications 9, 15 (October 2015), 1807-1811. https://doi.org/10.1049/iet-com.2014.1109
[7]
A. Deligiannis, A. Panoui, S. Lambotharan and J. A. Chambers. 2017. Game-Theoretic Power Allocation and the Nash Equilibrium Analysis for a Multistatic MIMO Radar Network. J. IEEE Transactions on Signal Processing 65, 24 (December 2017), 6397-6408. https://doi.org/10.1109/TSP.2017.2755591
[8]
D. Yang, G. Xue, J. Zhang, A. Richa and X. Fang. 2013. Coping with a Smart Jammer in Wireless Networks: A Stackelberg Game Approach. J. IEEE Transactions on Wireless Communications 12, 8 (August 2013), 4038-4047. https://doi.org/ 10.1109/TWC.2013.071913121570
[9]
Dejun Yang, Jin Zhang, Xi Fang, A. Richa and Guoliang Xue. 2012. Optimal transmission power control in the presence of a smart jammer. 2012 IEEE Global Communications Conference (GLOBECOM), Anaheim, CA, 5506-5511. https://doi.org/ 10.1109/GLOCOM.2012.6503997
[10]
A. Deligiannis, S. Lambotharan and J. A. Chambers. 2016. Game theoretic analysis for MIMO radars with multiple targets. J. IEEE Transactions on Aerospace and Electronic Systems 52, 6 (December 2016), 2760-2774. https://doi.org/ 10.1109/TAES.2016.150699
[11]
Z. Luo, W. Ma, A. M. So, Y. Ye and S. Zhang. 2010. Semidefinite Relaxation of Quadratic Optimization Problems. IEEE Signal Processing Magazine 27, 3 (May 2010), 20-34. https://doi.org/10.1109/MSP.2010.936019

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
ICIT '20: Proceedings of the 2020 8th International Conference on Information Technology: IoT and Smart City
December 2020
266 pages
ISBN:9781450388559
DOI:10.1145/3446999
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 April 2021

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Nash Equilibrium
  2. game theory
  3. multistatic radar
  4. power allocation

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Funding Sources

Conference

ICIT 2020
ICIT 2020: IoT and Smart City
December 25 - 27, 2020
Xi'an, China

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 30
    Total Downloads
  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)0
Reflects downloads up to 03 Mar 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media