Remote Sensing (Jul 2023)

Coalition Game Theoretic Power Allocation Strategy for Multi-Target Detection in Distributed Radar Networks

  • Xiangrong Dai,
  • Chenguang Shi,
  • Ziwei Wang,
  • Jianjiang Zhou

DOI
https://doi.org/10.3390/rs15153804
Journal volume & issue
Vol. 15, no. 15
p. 3804

Abstract

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This paper studies a coalition game theoretic power allocation algorithm for multi-target detection in radar networks based on low probability of intercept (LPI). The main goal of the algorithm is to reduce the total radiated power of the radar networks while satisfying the predetermined target detection performance of each radar. Firstly, a utility function that comprehensively considers both target detection performance and the radiated power of the radar networks is designed with LPI performance as the guiding principle. Secondly, it causes a coalition to form between cooperating radars, and radars within the same coalition share information. On this basis, a mathematical model for power allocation in radar networks based on coalition game theory is established. The model takes the given target detection performance as a constraint and maximizing system energy efficiency and optimal power allocation as the optimization objective. Furthermore, this paper proposes a game algorithm for joint coalition formation and power allocation in a multi-target detection scenario. Finally, the existence and uniqueness of the Nash equilibrium (NE) solution are proven through strict mathematical deduction. Simulation results validate the effectiveness and feasibility of the proposed algorithm.

Keywords