Detection of Multiple Stationary Humans Using UWB MIMO Radar

Liang, Fuyuan; Qi, Fugui; An, Qiang; Lv, Hao; Chen, Fuming; Zhao, Li; Wang, Jianqi

doi:10.3390/s16111922

Cited by 40 publications

(39 citation statements)

References 32 publications

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“…Besides background removing in preprocessing step, change detection (CD) algorithm is implemented to further enhance the vital signs as follows [14,24].…”

Section: Enhancement Of Vital Signsmentioning

confidence: 99%

“…The vital signs after CD can be seen as point-like targets in BP image [14]. According to [25], the kurtosis is proved to be a suitable metric to describe the contrast of an image mainly with point-like targets, and it is defined as…”

Section: Focusing Assessmentmentioning

confidence: 99%

“…The micro-motion-enhanced TWI imagery of stationary human being is focused on these human vital signs [12,13]. Through two-dimensional image, the shape and size of vital signs can be applied to detection, and two-dimensional localization can be obtained in the image [14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Through the Wall Imaging of Human Vital Signs Based on Uwb Mimo Bioradar

Liang¹,

Liu²,

Qi³

et al. 2018

PIER C

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Through-the-wall imaging (TWI) of human vital signs by bioradar is a hot research topic in recent years. Unknown wall parameters (mainly thickness and dielectric constant) are huge challenges for TWI. Ambiguities in wall parameters will degrade the image focusing quality, lower signal-to-noiseclutter ratio (SNCR) of vital signs, cause vital signs to be imaged away from their true positions and blur the close vital signs from multiple humans caused by the imaging resolution declination. A through-thewall propagation model of vital signs for multiple-input and multiple-output (MIMO) bioradar is first built to analyze the influence of wall on imaging. In order to obtain focused image of vital signs quickly, an imaging model and a novel autofocusing imaging method of vital signs are proposed in this paper. Since vital signs of human are weak and sensitive to interferences, the SNCR-enhanced imagery of vital signs after change detection (CD) is applied to evaluate the focusing quality of image. Reflections of wall in the stationary targets imaging result are line structure approximately, so Hough transform is used to extract the positions of the front edge and rear edge of wall automatically. Propagation time in the wall of electromagnetic waves is estimated and used to build the constraint relationship of wall parameters. The number of unknown parameters is reduced to only one and the efficiency of autofocusing imaging improves. Several cases, including the case of single human, multiple human objects close to each other and the case of non-human objects, are simulated. The magnetic resonance imaging (MRI) image of human chest is put into simulation scene. And then the simulation data of human vital signs are calculated by the finite-difference time-domain (FDTD) method. The results show that the proposed method can effectively estimate the wall parameters and improve the focusing performance of human vital signs. And also the kurtosis of image can be used as a feature to efficiently decide the human vital signs are existed or not. Thus the SNCR of vital signs and resolution of imaging are improved, which are beneficial for detection of vital signs. The position errors of human vital signs are also corrected.

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“…Besides background removing in preprocessing step, change detection (CD) algorithm is implemented to further enhance the vital signs as follows [14,24].…”

Section: Enhancement Of Vital Signsmentioning

confidence: 99%

Section: Focusing Assessmentmentioning

confidence: 99%

See 1 more Smart Citation

Through the Wall Imaging of Human Vital Signs Based on Uwb Mimo Bioradar

Liang¹,

Liu²,

Qi³

et al. 2018

PIER C

Self Cite

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show abstract

“…The high-range resolution of IR-UWB radars has been applied to various fields such as detection, location estimation, tracking, recognition, and bio-signal measurement. There have been studies for detecting, estimating, and tracking humans [15][16][17][18][19][20] and further studies for detecting multiple humans [21][22][23]. They are also used in the field of cognition, where they have been used for studies on distinguishing human body movements including hand gestures and mouth movements [24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Lane Detection Method with Impulse Radio Ultra-Wideband Radar and Metal Lane Reflectors

Kim

2020

Sensors

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An advanced driver-assistance system (ADAS), based on lane detection technology, detects dangerous situations through various sensors and either warns the driver or takes over direct control of the vehicle. At present, cameras are commonly used for lane detection; however, their performance varies widely depending on the lighting conditions. Consequently, many studies have focused on using radar for lane detection. However, when using radar, it is difficult to distinguish between the plain road surface and painted lane markers, necessitating the use of radar reflectors for guidance. Previous studies have used long-range radars which may receive interference signals from various objects, including other vehicles, pedestrians, and buildings, thereby hampering lane detection. Therefore, we propose a lane detection method that uses an impulse radio ultra-wideband radar with high-range resolution and metal lane markers installed at regular intervals on the road. Lane detection and departure is realized upon using the periodically reflected signals as well as vehicle speed data as inputs. For verification, a field test was conducted by attaching radar to a vehicle and installing metal lane markers on the road. Experimental scenarios were established by varying the position and movement of the vehicle, and it was demonstrated that the proposed method enables lane detection based on the data measured.

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“…Therefore, many studies on implementing CMOS radar transceiver [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ] have been actively conducted, recently. In addition, studies on signal processing algorithms that improve the performance of radar sensors have also been carried out [ 13 , 14 , 15 , 16 , 17 , 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Design of Dual-Mode Local Oscillators Using CMOS Technology for Motion Detection Sensors

Lee

Kim

et al. 2018

Sensors

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Recently, studies have been actively carried out to implement motion detecting sensors by applying radar techniques. Doppler radar or frequency-modulated continuous wave (FMCW) radar are mainly used, but each type has drawbacks. In Doppler radar, no signal is detected when the movement is stopped. Also, FMCW radar cannot function when the detection object is near the sensor. Therefore, by implementing a single continuous wave (CW) radar for operating in dual-mode, the disadvantages in each mode can be compensated for. In this paper, a dual mode local oscillator (LO) is proposed that makes a CW radar operate as a Doppler or FMCW radar. To make the dual-mode LO, a method that controls the division ratio of the phase locked loop (PLL) is used. To support both radar mode easily, the proposed LO is implemented by adding a frequency sweep generator (FSG) block to a fractional-N PLL. The operation mode of the LO is determined by according to whether this block is operating or not. Since most radar sensors are used in conjunction with microcontroller units (MCUs), the proposed architecture is capable of dual-mode operation by changing only the input control code. In addition, all components such as VCO, LDO, and loop filter are integrated into the chip, so complexity and interface issues can be solved when implementing radar sensors. Thus, the proposed dual-mode LO is suitable as a radar sensor.

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Detection of Multiple Stationary Humans Using UWB MIMO Radar

Cited by 40 publications

References 32 publications

Through the Wall Imaging of Human Vital Signs Based on Uwb Mimo Bioradar

Through the Wall Imaging of Human Vital Signs Based on Uwb Mimo Bioradar

Lane Detection Method with Impulse Radio Ultra-Wideband Radar and Metal Lane Reflectors

Design of Dual-Mode Local Oscillators Using CMOS Technology for Motion Detection Sensors

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