Through-the-Wall Sensing of Personnel Using Passive Bistatic WiFi Radar at Standoff Distances

Chetty, Kevin; Smith, Gerald Birney; Woodbridge, K.

doi:10.1109/tgrs.2011.2164411

Cited by 216 publications

(168 citation statements)

References 27 publications

Supporting

Mentioning

158

Contrasting

Order By: Relevance

“…Other drift-free sensors, such as ultrasound, short-range radio -ultra-wideband (UWB) [87]- [90], radio frequency identification (RFID) [91], Wi-Fi [92] [93], and Zigbee [94] -have also been explored in recent years. Regardless of the drift-free sensor type, the addition of complementary data from extra sensors has been shown to be effective towards reducing measurement drift from inertial sensing.…”

Section: B Processing Techniquesmentioning

confidence: 99%

Wearable Sensing for Solid Biomechanics

Wong

Zhang

et al. 2015

IEEE Sensors J.

View full text Add to dashboard Cite

Abstract-Understanding the solid biomechanics of the human body is important to the study of structure and function of the body, which can have a range of applications in healthcare, sport, wellbeing, and workflow analysis. Conventional laboratorybased biomechanical analysis systems and observation-based tests are only designed to capture brief snapshots of the mechanics of movement. With recent developments in wearable sensing technologies, biomechanical analysis can be conducted in less constrained environments, thus allowing continuous monitoring and analysis beyond laboratory settings. In this paper, we review the current research in wearable sensing technologies for biomechanical analysis, focusing upon sensing and analytics that enable continuous, long-term monitoring of kinematics and kinetics in a free-living environment. The main technical challenges, including measurement drift, external interferences, nonlinear sensor properties, sensor placement, and muscle variations that can affect the accuracy and robustness of existing methods, and different methods for reducing the impact of these sources of errors are described in this review. Recent developments in motion estimation in kinematics, mobile force sensing in kinematics, sensor reduction for electromyography, as well as the future direction of sensing for biomechanics are also discussed.

show abstract

Section: B Processing Techniquesmentioning

confidence: 99%

Wearable Sensing for Solid Biomechanics

Wong

Zhang

et al. 2015

IEEE Sensors J.

View full text Add to dashboard Cite

show abstract

“…In receive, th low pass filtering, allowing the recorded dat via the USRP's gigabit Ethernet port to imultaneously on ata that streams subroutine should roximately equal environment in sign that facilitates ng in the wireless hm is divided into e and surveillance essing on this data applying CLEAN ed in [11]. Figure 3 may be written as (3) which is same as are the processing tion (3), is n, cannot be reduce ift time in Figure 1 In order to build a should not be erence and noise thus, it is easy to of the ambiguity g sequence cross which cause long equence, that often cessing delay ocessing.…”

Section: ) Pipeline Processing Flmentioning

confidence: 99%

A real-time high resolution passive WiFi Doppler-radar and its applications

Tan

Woodbridge

Chetty

2014

2014 International Radar Conference

Self Cite

View full text Add to dashboard Cite

Abstract-The design and implementation of a real-time passive high Doppler resolution radar system is described in this paper. Batch processing and pipelined processing flow are introduced for reducing the processing time to enable real-time display. The proposed method is implemented on a software defined radio (SDR) platform. Two experiments using this system are described: one based on small human body motions and another one on hand gesture detection. The results from these experiments show that the proposed system can be used in a range of application scenarios such as eHealth, human-machine interaction and high accuracy indoor target tracking.

show abstract

“…Hardware innovations in this area include active MIMO array systems [5] providing cross range information, ultra-wide band radars [6], [7] [8] for high range resolution, Synthetic Aperture Radar (SAR) imaging techniques [9] and passive WiFi 2 of 17 radar [10]. The practical implications of using a MIMO radar for TTW imaging is discussed in [11].…”

Section: Introductionmentioning

confidence: 99%

Through Wall Radar Classification of Human Micro-Doppler using Singular Value Decomposition Analysis

Ritchie

Ash

Chen

et al. 2016

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract:The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques.

show abstract

Through-the-Wall Sensing of Personnel Using Passive Bistatic WiFi Radar at Standoff Distances

Cited by 216 publications

References 27 publications

Wearable Sensing for Solid Biomechanics

Wearable Sensing for Solid Biomechanics

A real-time high resolution passive WiFi Doppler-radar and its applications

Through Wall Radar Classification of Human Micro-Doppler using Singular Value Decomposition Analysis

Contact Info

Product

Resources

About