Integrated Sensing, Communication, and Control for UAV-Assisted Mobile Target Tracking
Zhiyu Chen, Ming-Min Zhao, Songfu Cai, Ming Lei, and Min-Jian Zhao

TL;DR
This paper introduces an integrated framework combining sensing, communication, and control for UAVs to improve target tracking accuracy, communication stability, and control efficiency through a novel optimization approach.
Contribution
It proposes a unified ISCC framework with a tractable control-oriented optimization method for UAV-assisted target tracking, integrating beamforming and control design.
Findings
Achieves tracking accuracy comparable to non-causal benchmarks.
Maintains stable communication during tracking.
Outperforms conventional control and tracking methods.
Abstract
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…
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Taxonomy
TopicsDistributed Control Multi-Agent Systems · UAV Applications and Optimization · Adaptive Dynamic Programming Control
