A Binary Sparrow-Hybridized Beluga Whale Optimization Algorithm for Jamming Task Assignment

In the context of non-cooperative electronic countermeasures, the problem of formulating effective jamming task assignments arises due to insufficient collaborative jamming resources. This paper proposes a binary sparrow- hybridized beluga whale optimization algorithm based on jamming task assignments. The algorithm combines the binary sparrow search algorithm(BSSA) and the binary beluga whale optimization(BBWO), which is set with multi-dimensional constraints in the time, frequency and spatial domains. To achieve the optimal strategy for collaborative interference task assignment, a fitness function is constructed using both radar coverage and the signal-to-jamming ratio received by each radar. When the number of UAVs is 7 and the number of radars is 10, the simulation results show that the optimization speed and accuracy of the proposed algorithm are significantly higher than the BSSA and BBWO. Therefore, the algorithm has good coverage and performance in the field of jamming task assignments.