IHHO-based joint optimization of path and jamming resources for penetration missions

To address the issue of independent decision-making in current penetration mission planning, this paper proposes a joint optimization model based on a “path–jamming–decision closed-loop integration.” A path cost function is constructed considering three dimensions—length, threat, and smoothness—while the jamming effectiveness value is calculated using a weighted approach across the three stages of radar operation—search, positioning, and tracking. A multi-objective fitness function is then established. To solve this model, an Improved Harris Hawks Optimization (IHHO) algorithm is introduced, which incorporates the mechanisms of the particle swarm optimization algorithm into its phased predatory behavior, enabling coordinated decision-making for both path and jamming resource allocation. Simulation results show that the penetration paths planned by this method can effectively avoid radar threats and obstacles, achieving low-cost penetration. Moreover, the jamming effectiveness value increases steadily as the penetration progresses, significantly improving the utilization efficiency of jamming resources. Compared to other algorithms, IHHO also demonstrates advantages in convergence speed, robustness, and computational efficiency.