AoI-Optimal Multi-AAV-Enabled ISAC for Target Detection and Data Collection in Wireless Sensor Networks

Unmanned aerial vehicles (UAVs) have been widely applied to target detection or data collection tasks in wireless sensor networks (WSNs). However, few existing studies considered resource overhead associated with the collaborative execution of both tasks. To overcome this limitation, this paper proposes a multi-UAV-enabled integrated sensing and communication (ISAC) scheme for WSNs. Each UAV serves as a dual-functional aerial platform for target detection and data collection. Considering non-simultaneous sensing and communication operations, we design a novel ISAC frame structure to optimize sensing and communication time allocation. To measure data freshness, the age of information (AoI) is introduced as a critical metric, while probability of detection (PD) is used to evaluate the sensing performance. We formulate a joint optimization problem to minimize the average AoI of sensors under the constraint of PD by coordinating UAV-sensor association, UAV flight trajectory, sensing and communication time allocation, sensing beamwidth, and UAV flight altitude. To tackle the non-convex mixed-integer programming challenge, the optimization problem is decomposed into four subproblems, for which we propose a multiple traveling salesman problem-based data collection scheduling strategy and develop a three-layer alternating optimization algorithm. Simulation results show that the proposed algorithm reduces the average AoI and total sensing time by up to 19% and 77%, respectively, compared to baseline schemes. Furthermore, for a fixed PD value, multi-UAV standalone sensing (SS) improves AoI performance by 38% over multi-UAV cooperative sensing (CS). In contrast, multi-UAV CS reduces the total sensing time by 40% compared to multi-UAV SS.