Map-Fusion based Multi-Target Tracking in Cooperative ISAC Networks

The Integrated Sensing and Communication (ISAC) technique combines communication and environmental sensing in future wireless networks. Since multi-static sensing advantages in spatial diversity, cooperative ISAC networks have garnered extensive attention and investigation, but face challenges such as separation, extraction, and cooperative fusion of multi-target sensing information. To address these challenges, a code division approach is proposed to differentiate targets and signal source base stations. Furthermore, a map-fusion based cooperating localization approach integrating Direction of Arrival (DOA) estimation is introduced. Finally, numerical simulations validate the effectiveness of the proposed approaches. Code division reduces the Root Mean Squared error (RMSE) for angle, range, and velocity estimation by 86.4%, 91.7%, and 52.4% compared to the baseline approach. Additionally, the map-fusion based approach reduces localization RMSE by 83.4% to 95.1% compared to the existing localization approaches.

Map-Fusion based Multi-Target Tracking in Cooperative ISAC Networks

Zihe Wang, Ning Jiang, Shi Yan, Beijing University of Posts and Telecommunications