Integrated Sensing, Communication, and Control for UAV-Assisted Mobile Target Tracking

Unmanned aerial vehicles (UAVs) are increasingly deployed in mission-critical applications such as target tracking, where they must simultaneously sense dynamic environments, ensure reliable communication, and achieve precise control. A key challenge here is to jointly guarantee tracking accuracy, communication reliability, and control stability within a unified framework. To address this issue, we propose an integrated sensing, communication, and control (ISCC) framework for UAV-assisted target tracking, where the considered tracking system is modeled as a discrete-time linear control process, with the objective of driving the deviation between the UAV and target states toward zero. We formulate a stochastic model predictive control (MPC) optimization problem for joint control and beamforming design, which is highly non-convex and intractable in its original form. To overcome this difficulty, the target state is first estimated using an extended Kalman filter (EKF). Then, by deriving the closed-form optimal beamforming solution under a given control input, the original problem is equivalently reformulated into a tractable control-oriented form. Finally, we convexify the remaining non-convex constraints via a relaxation-based convex approximation, yielding a computationally tractable convex optimization problem that admits efficient global solution. Numerical results show that the proposed ISCC framework achieves tracking accuracy comparable to a non-causal benchmark while maintaining stable communication, and it significantly outperforms the conventional control and tracking method.

💡 Research Summary

The paper addresses the challenging problem of simultaneously tracking a moving target and providing reliable downlink communication to a ground user (GU) using an unmanned aerial vehicle (UAV). To meet the stringent requirements of future 6G integrated sensing and communication (ISAC) systems, the authors propose an Integrated Sensing, Communication, and Control (ISCC) framework that tightly couples the three functions within a single optimization problem.

System Modeling
The authors discretize the mission time into N slots and assume that within each slot the horizontal positions and velocities of both the UAV and the target remain constant. The UAV is equipped with a uniform planar antenna array (UPA) and transmits a single waveform that serves both as a communication signal and as a radar probing signal. The communication channel to the GU is modeled as a line‑of‑sight (LoS) link with a steering vector that depends on the UAV‑GU geometry. The radar echo is modeled by a range‑Doppler measurement that yields distance and velocity information about the target. Both measurements are corrupted by additive white Gaussian noise.

Control‑Centric State Definition
The tracking error (UAV state minus target state) is defined as the system state x