ISAC Empowered Air-Sea Collaborative System: A UAV-USV Joint Inspection Framework

TL;DR

The paper addresses energy-efficient ISAC-enabled maritime inspection using a coordinated UAV-USV system. It develops a two-subproblem framework that first selects hover points and schedules targets, then jointly optimizes UAV/USV trajectories and ISAC beamforming via SDR/SCA in each stage. A three-step hover-point method (VBSC clustering, Bi-TSPN visiting order, hover-point refinement/time allocation) and an alternating optimization approach for flying/hovering modes enable tractable solutions and show substantial energy savings over sequential access and leader–follower baselines. The work highlights how target distribution, S&C requirements, and water currents influence energy efficiency and task duration, offering a practical path to energy-conscious ISAC-enabled air-sea operations with potential extensions to edge computing and UAV charging on USV platforms.

Abstract

In this paper, we construct an air-sea collaborative system framework based on the Integrated Sensing and Communication (ISAC) techniques, where the Unmanned Aerial Vehicle (UAV) and Unmanned Surface Vehicle (USV) jointly inspect targets of interest while keeping communication with each other simultaneously. First, we demonstrate the unique challenges encountered in this collaborative system, i.e., the coupling and heterogeneity of the UAV/USV's trajectories. Then, we formulate a total energy consumption minimization problem to jointly optimize the trajectories, flying and hovering times, target scheduling, and beamformers under the constraints of water currents, collision avoidance, and Sensing and Communication (S\&C) requirements. To address the strong coupling of the variables, we divide the original problem into two subproblems, namely, the hover point selection and the joint trajectory planning and beamforming design. In the first subproblem, we propose a three-step hierarchical method including: (1) a virtual base station coverage (VBSC) and clustering algorithm to obtain the target scheduling and rough position of hover points; (2) a Bi-traveling salesman problem with neighborhood (Bi-TSPN)-based algorithm to determine the visiting order sequence of the hover points; (3) a hover point refinement and time allocation algorithm to further optimize the time allocation. In the latter subproblem, we complete the remaining trajectory planning and beamforming design in each flying and hovering stage by developing a semi-definite relaxation (SDR) and successive convex approximation (SCA) method. Finally, we conduct a series of simulations to demonstrate the superiority of the proposed scheme over existing sequential access and leader-follower strategies.

Figures (15)

• Figure 1: Maritime inspection system.
• Figure 2: ISAC time slot structure.
• Figure 3: Flow of the problem solution.
• Figure 4: Diagram of UAV and USV trajectories in our flying and hovering scheme.
• Figure 5: The diagram for the three-step hierarchical hover point selection method.