Enabling Indoor Multi-Person Tracking With 6G mmWave ISAC Systems
Chongrui Wang, Aimin Tang, Fei Gao, Chaojun Xu

TL;DR
This paper presents a novel 6G mmWave ISAC system for indoor multi-person tracking, utilizing sparse sensing signals and advanced algorithms to achieve high accuracy with minimal sensing overhead.
Contribution
It introduces a new multi-person tracking method with low sensing overhead, combining a modified MTI scheme, target identification, and Kalman filtering with data association.
Findings
Median position error of 12 cm in indoor environments
Sensing overhead less than 0.005% of OFDM frame
Effective tracking during path-crossing scenarios
Abstract
Integrated sensing and communication (ISAC) has emerged as a key technology for 6G wireless networks. In this paper, wireless sensing for the indoor multi-person tracking is explored with 6G mmWave ISAC systems. To limit the sensing overhead, a sparse deployment of sensing reference signals (RS) is applied in the orthogonal frequency-division multiplexing (OFDM) frame, where the channel state information (CSI) at the sensing RS is extracted for the multi-person tracking. To enable a robust tracking of multiple persons in a complex indoor environment, three key mechanisms are proposed: 1) a modified moving target indicator (MTI) scheme is proposed to remove the static environmental clutter under a sparse RS time spacing; 2) an effective target identification mechanism is developed to exclude false target points; 3) the Kalman filter with a penalty association algorithm is designed to…
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