Contact-Free Multitarget Tracking Using Distributed Massive MIMO-OFDM Communication System: Prototype and Analysis

Abstract

Wireless-based human activity recognition has become an essential technology that enables contact-free humanmachine and human-environment interactions. In this paper, we consider contact-free multi-target tracking (MTT) based on available communication systems. A radar-like prototype is built upon a sub-6 GHz distributed massive multiple-input and multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) communication system. Specifically, the raw channel state information (CSI) is calibrated in the frequency and antenna domain before being used for tracking. Then the targeted CSIs reflected or scattered from the moving pedestrians are extracted. To evade the complex association problem of distributed massive MIMO-based MTT, we propose to use a complex Bayesian compressive sensing (CBCS) algorithm to estimate the targets' locations based on the extracted target-ofinterest CSI signal directly. The estimated locations from CBCS are fed to a Gaussian mixture probability hypothesis density (GM-PHD) filter for tracking. A multi-pedestrian tracking experiment is conducted in a room with a size of 6.5 m×10 m to evaluate the performance of the proposed algorithm. According to experimental results, we achieve 75th and 95th percentile accuracy of 12.7 cm and 18.2 cm for single-person tracking and 28.9 cm and 45.7 cm for multi-person tracking, respectively. Furthermore, the proposed algorithm achieves tracking purposes in real-time, which is promising for practical MTT use cases.

Device-Free Tracking through Self-Attention Mechanism and Unscented Kalman Filter with Commodity Wi-Fi

“…Moreover, traditional approaches require subjects to wear sensors or transceiver-equipped, which are then localized to the sensors rather than the wearer through observing changes and the fluctuating received signals into a coordinate system [ 22 , 23 , 24 ]. The other drawback of using traditional methods such as received signal strength indicator (RSSI) compared to channel state information (CSI) is that RSSI measurements are per a single packet value [ 8 , 25 , 26 , 27 , 28 ].…”