An initial population optimization-based particle swarm algorithm for anti-jamming communication decision engines

To improve the real-time performance of anti-jamming decision making, this paper proposes an initial population optimization particle swarm algorithm (IPO-PSO). This algorithm utilizes a portion of the solution from the previous decision as the initial population in the current decision; thus optimizes the adaptive quality of the initial population used for the current decision. The simulation results show that the proposed method can increase the convergence rate of the particle swarm optimization algorithm without increasing the complexity. Thus, this method provides impressive real-time performance and is ideally suited for demanding applications such as in military antijamming communications systems.