Collaborative Detection Planning Algorithm in Airborne Radar Network Based on Mission Utility

In this paper, we propose a collaborative detection planning algorithm in airborne radar network based on mission utility. The basis of the proposed algorithm is to adaptively optimizes the assignment results of mission-radar node selection parameters, in order to maximize the global utility of airborne radar network in collaborative detection mission allocation, while satisfying the constraints of the given limitations of the maximum available time resources, echo signal-to-noise ratio (SNR) and system performance. Furthermore, we derive the global utility function of airborne radar network within a mission quality framework, and ulteriorly employ it as the criterion function to evaluate the multi-mission integrated execution efficiency. By incorporating the interior point method, we develop a three-step solution methodology to address the aforementioned optimization problem efficiently. Numerical simulations validate the superiority and reliability of our proposed algorithm in terms of mission utility, outperforming existing approaches.