Indoor Tracking of Multiple Individuals With an 802.11ax Wi-Fi-Based Multi-Antenna Passive Radar

Storrer, Laurent; Yildirim, Hasan Can; Crauwels, Morgane; Copa, Evert I. Pocoma; Pollin, Sofie; Louveaux, Jérôme; Doncker, Philippe De; Horlin, François

doi:10.1109/jsen.2021.3095675

Cited by 19 publications

(10 citation statements)

References 19 publications

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“…We name it evolving association. According to the authors' best knowledge, there are also a few works on CSI-based multi-person tracking [7], [8], [23]. Besides the location-or velocity-related parameters extraction as in single-person tracking, we need to assign the estimated MPCs to the corresponding targets as we have no idea of which targets that MPCs are generated from.…”

Section: B Practical Challengesmentioning

confidence: 99%

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

Bast

Miao

et al. 2023

IEEE Internet Things J.

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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.

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Section: B Practical Challengesmentioning

confidence: 99%

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

Bast

Miao

et al. 2023

IEEE Internet Things J.

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“…Sensing through Wi-Fi networks aims at utilizing Wi-Fi signals to detect and sense targets, such as people, animals, objects, and/or locations of interest. While the feasibility of using Wi-Fi to enable sensing has been demonstrated over the past several years [4][5][6][7][8][9], the range of applications that is currently supported is limited due to the lack of sensingspecific features in the IEEE 802.11 standard, hindering the usage of multiple 802.11 devices from different vendors for sensing applications. For this reason, Task Group IEEE 802.11bf (TGbf) started in September 2020 the development of an amendment to the IEEE 802.11 standard supporting sensing [10].…”

Section: Introductionmentioning

confidence: 99%

IEEE 802.11bf DMG Sensing: Enabling High-Resolution mmWave Wi-Fi Sensing

Blandino

Ropitault

Silva

et al. 2023

IEEE Open J. Veh. Technol.

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IEEE 802.11bf amendment is defining the wireless Local Area Network (WLAN) sensing procedure, which supports sensing in license-exempt frequency bands below 7 GHz, and the Directional Multi-Gigabit (DMG) sensing procedure for license-exempt frequency bands above 45 GHz. In this paper, we examine the use of Millimeter-Wave (mmWave) Wi-Fi to enable high-resolution sensing. We first provide an introduction to the principle of sensing and the modifications defined by the IEEE 802.11bf amendment to IEEE 802.11 to enable mmWave Wi-Fi sensing. We then present a new open-source framework that we develop to enable the evaluation of the DMG sensing procedure accuracy. We finally quantify the performance of the DMG sensing in terms of the velocity/angle estimate accuracy, and its overhead on the communication link. Results show that the DMG sensing procedure defined in IEEE 802.11bf is flexible enough to accommodate a wide range of sensing applications. For the bistatic scenario considered, the velocity accuracy is in the interval 0.1 m/s to 0.4 m/s, while the angular accuracy is between 1 degree and 8 degrees depending on the sensing parameters used. Ultimately, the overhead introduced by sensing is limited with a sensing overhead below 5.5 % of the system symbol rate.

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“…Through the integration of sensing and communication functionalities on a common platform, JRC based connected systems offer the advantages of increased spectral efficiency through shared spectrum and reduced hardware costs. The most common applications are WiFi/WLAN based indoor detection of humans Falcone et al (2012); Storrer et al (2021); Tan et al (2016); Li et al (2020); Alloulah and Huang (2019); Yildirim et al (2021), radar enhanced vehicular communications Ali et al (2020); Kumari et al (2017); Dokhanchi et al (2019); Duggal et al (2020), covert communications supported by radar based localization Kellett et al (2019); Hu et al (2019) and radar remote sensing based on global navigation satellite systems (GNSS) Zavorotny et al (2014). All of these systems consist of a dual functional (radar-communication) transmitter and either a standalone or integrated radar/ communications receiver.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Network Throughput of Joint Radar Communication System Using Stochastic Geometry

Ram

Singhal

Ghatak

2022

Front. Signal Process.

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Recently joint radar communication (JRC) systems have gained considerable interest for several applications such as vehicular communications, indoor localization and activity recognition, covert military communications, and satellite based remote sensing. In these frameworks, bistatic/passive radar deployments with directional beams explore the angular search space and identify mobile users/radar targets. Subsequently, directional communication links are established with these mobile users. Consequently, JRC parameters such as the time trade-off between the radar exploration and communication service tasks have direct implications on the network throughput. Using tools from stochastic geometry (SG), we derive several system design and planning insights for deploying such networks and demonstrate how efficient radar detection can augment the communication throughput in a JRC system. Specifically, we provide a generalized analytical framework to maximize the network throughput by optimizing JRC parameters such as the exploration/exploitation duty cycle, the radar bandwidth, the transmit power and the pulse repetition interval. The analysis is further extended to monostatic radar conditions, which is a special case in our framework. The theoretical results are experimentally validated through Monte Carlo simulations. Our analysis highlights that for a larger bistatic range, a lower operating bandwidth and a higher duty cycle must be employed to maximize the network throughput. Furthermore, we demonstrate how a reduced success in radar detection due to higher clutter density deteriorates the overall network throughput. Finally, we show a peak reliability of 70% of the JRC link metrics for a single bistatic transceiver configuration.

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Indoor Tracking of Multiple Individuals With an 802.11ax Wi-Fi-Based Multi-Antenna Passive Radar

Cited by 19 publications

References 19 publications

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

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

IEEE 802.11bf DMG Sensing: Enabling High-Resolution mmWave Wi-Fi Sensing

Optimization of Network Throughput of Joint Radar Communication System Using Stochastic Geometry

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