Cooperative game-theoretic power allocation algorithm for target detection in radar network

This paper investigates the problem of power allocation for radar network in a cooperative game-theoretic framework such that the low probability of intercept (LPI) performance can be improved. Taking into consideration both the transmit power constraint and the minimum signal-to-interference-plus-noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game (NBPAG) based on LPI is formulated, whose objective is to improve the LPI performance by optimizing the transmit power allocation in radar network for a predefined S-INR threshold. First, a novel SINR-based network utility function is defined as a metric to evaluate power allocation. Then, the existence and uniqueness of the Nash bargaining solution (NBS) are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Theoretic analysis and simulations are provided to evaluate the effectiveness of the proposed algorithm.