UAV-Enabled Integrated Sensing and Communication: Tracking Design and Optimization

Integrated sensing and communications (ISAC) enabled by unmanned aerial vehicles (UAVs) is a promising technology to facilitate target tracking applications. In contrast to conventional UAV-based ISAC system designs that mainly focus on estimating the target position, the target velocity estimation...

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Bibliographic Details
Published in:IEEE communications letters 2024-05, Vol.28 (5), p.1024-1028
Main Authors: Jiang, Yifan, Wu, Qingqing, Chen, Wen, Meng, Kaitao
Format: Article
Language:English
Subjects:
Approximation
Autonomous aerial vehicles
Covariance matrices
Cramer-Rao bounds
CRB
Design optimization
Elevation angle
Error analysis
Estimation
ISAC
Kalman filters
Moving object recognition
Noise measurement
Resource allocation
Sensors
Target tracking
Time measurement
Time response
Tracking
Trajectory
UAV
Unmanned aerial vehicles
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Summary:Integrated sensing and communications (ISAC) enabled by unmanned aerial vehicles (UAVs) is a promising technology to facilitate target tracking applications. In contrast to conventional UAV-based ISAC system designs that mainly focus on estimating the target position, the target velocity estimation also needs to be considered due to its crucial impacts on link maintenance and real-time response, which requires new designs on resource allocation and tracking scheme. In this letter, we propose an extended Kalman filtering-based tracking scheme for a UAV-enabled ISAC system where a UAV tracks a moving object and also communicates with a device attached to the object. Specifically, a weighted sum of predicted posterior Cramér-Rao bound (PCRB) for object relative position and velocity estimation is minimized by optimizing the UAV trajectory, where an efficient solution is obtained based on the successive convex approximation method. Furthermore, under a special case with the measurement mean square error (MSE), the optimal relative motion state is obtained and proved to keep a fixed elevation angle and zero relative velocity. Numerical results validate that the solution to the predicted PCRB minimization can be approximated by the optimal relative motion state when predicted measurement MSE dominates the predicted PCRBs, as well as the effectiveness of the proposed tracking scheme. Moreover, three interesting trade-offs on system performance resulted from the fixed elevation angle are illustrated.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2024.3379504