Underwater multi-target tracking is one of the key technologies for military missions, including patrol and combat in the crucial area. Since the underwater environment is complex and targets’ trajectories may intersect when they are in a dense area, it is challenging to guarantee the precision of observed information. In order to provide high-precision underwater localization and tracking services over an underwater monitoring network, a dynamic network resource allocation mechanism and an underwater multi-target tracking algorithm based on a two-layer particle filter with distributed probability fusion (TLPF-DPF) are proposed. The position estimation model based on geometric constraints and the dynamic allocation mechanism of network resources based on prior position estimation are designed. Using the improved filtering algorithm with known initial states, the reliable tracking of multiple targets with trajectory intersection in a small area under complex noises is achieved. In the non-Gaussian environment, the average positioning error of TLPF-DPF is less by nearly 30% than alternative algorithms. When switching from a Gaussian environment to a non-Gaussian environment, the performance degradation of TLPF-DPF is less than 12%, which exhibits stability compared with other algorithms when targets are close to each other with crossing trajectories.

In order to achieve the precise attack of multiple underwater intelligent vehicles (UIVs) on the same target ship at a fixed impact time, and to improve the penetration capability of the UIVs themselves, this study investigated the guidance law for the time-cooperative guidance of UIVs with maneuvering evasion. The evasive maneuver of the UIV increases the line-of-sight angle between the UIV and the target, which decreases the guidance precision of the UIV. A segmented control strategy is proposed to solve the problem of decreasing guidance precision caused by evading maneuvers, which is also the main contribution of this paper. This control strategy is dividing the guidance trajectory into two segments. The first segment allows for intelligent underwater vehicles to make evasion maneuvers and penetrate the defense, while the second segment controls the terminal time and achieves precision strike. Different desired target-vehicle distances are designed for each segment, unifying the impact time control issue and evasion maneuver problem into the pursuit of desired target-vehicle distances. Finally, based on feedback linearization control theory, a time-cooperative guidance law with evasion maneuver capability is proposed. Simulation results validate the effectiveness of the proposed method in attacking-moving targets.