TY - JOUR
T1 - Data Association for Moving Multitarget Sensing in Distributed OTFS Radars
AU - Li, Buyi
AU - He, Dongxuan
AU - Tao, Qin
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2026
Y1 - 2026
N2 - Aerial drones in wireless communication systems offer rapid deployment, flexible reconfiguration, and superior communication channels, thanks to their short-range line-of-sight links, making them more efficient and cost-effective than terrestrial or high-altitude platform networks. As a promising technique, integrated sensing and communication (ISAC) enhances aerial drones networks by integrating sensing and communication functionalities. This concurrent design improves spectrum efficiency and reduces hardware costs. To ensure reliable communication for their high mobility, a novel modulation technique, the orthogonal time-frequency space (OTFS) waveform, has been proposed, which leverages the delay-Doppler domain for efficient information transmission. In this article, we investigate ISAC-based multitarget sensing with distributed OTFS radars to deliver reliable performance for aerial drones networks. To achieve that, we propose to leverage the delay and Doppler information featured by OTFS signals to determine the range and radial velocity, accomplishing successful sensing tasks. Moreover, to address the challenge of unassociated measurements and targets, we propose a novel optimization framework to concurrently perform data association and target sensing tasks. This framework is developed by formulating a mixed-integer optimization problem, which is then solved with polynomial complexity through convex approximation. Additionally, we propose an iterative maximum likelihood estimator (MLE) to further enhance sensing performance by accounting for target-measurement errors. Extensive simulation results verify the superiority of our proposed work to state-of-the-art methods.
AB - Aerial drones in wireless communication systems offer rapid deployment, flexible reconfiguration, and superior communication channels, thanks to their short-range line-of-sight links, making them more efficient and cost-effective than terrestrial or high-altitude platform networks. As a promising technique, integrated sensing and communication (ISAC) enhances aerial drones networks by integrating sensing and communication functionalities. This concurrent design improves spectrum efficiency and reduces hardware costs. To ensure reliable communication for their high mobility, a novel modulation technique, the orthogonal time-frequency space (OTFS) waveform, has been proposed, which leverages the delay-Doppler domain for efficient information transmission. In this article, we investigate ISAC-based multitarget sensing with distributed OTFS radars to deliver reliable performance for aerial drones networks. To achieve that, we propose to leverage the delay and Doppler information featured by OTFS signals to determine the range and radial velocity, accomplishing successful sensing tasks. Moreover, to address the challenge of unassociated measurements and targets, we propose a novel optimization framework to concurrently perform data association and target sensing tasks. This framework is developed by formulating a mixed-integer optimization problem, which is then solved with polynomial complexity through convex approximation. Additionally, we propose an iterative maximum likelihood estimator (MLE) to further enhance sensing performance by accounting for target-measurement errors. Extensive simulation results verify the superiority of our proposed work to state-of-the-art methods.
KW - Aerial drone
KW - data association
KW - integrated sensing and communication (ISAC)
KW - multitarget sensing
KW - orthogonal time-frequency space (OTFS)
UR - https://www.scopus.com/pages/publications/105007987590
U2 - 10.1109/JIOT.2025.3578819
DO - 10.1109/JIOT.2025.3578819
M3 - Article
AN - SCOPUS:105007987590
SN - 2327-4662
VL - 13
SP - 5544
EP - 5555
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 4
ER -