UWB radar for human being detection

Varovoy, A.G.; Ligthart, L.P.; Matuzas, J.; Levitas, B.

doi:10.1109/maes.2006.1624185

Cited by 119 publications

(25 citation statements)

References 5 publications

(2 reference statements)

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“…Note that image X and Y can have different size N X and N Y , since mutual information is only relevant to histograms. Finally, mutual information can be derived by (1), (2) and (4) as…”

Section: Vtdfmentioning

confidence: 99%

“…Detection and localisation of people inside buildings is an important issue for security [1,2], and multistatic radar is a privileged tool for such applications, because of its ability to increase observability and cover large area. Such a multistatic radar usually consists of one transmitting antenna and multiple receiving antennas, which are distributed in different locations of the monitored area.…”

Section: Introductionmentioning

confidence: 99%

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Decentralised tracking for human target in multistatic ultra‐wideband radar

Aubry

Chevalier

et al. 2014

IET Radar, Sonar & Navigation

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A global signal processing chain for detection and localisation of moving human targets using a multistatic ultrawideband radar system with widely separated receiving antennas is proposed. The design options for the system are presented and justified, and the required signal processing steps are summarised. Special attention is then devoted to the critical issue of target association. A slow-time feature, video time density function, is proposed to associate target responses in different receiver channels. Video time density function is extracted from range-Doppler video sequences for each target. It indicates the slow-time evolution characteristic of the moving human targets, and thus is invariant to radar observation angles (provided that the target can be detected). Auction algorithm-based global nearest neighbour approach is extended to the measurement-to-measurement association between receivers. The decentralised tracking approach proposed is experimentally verified on measured data.

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“…Note that image X and Y can have different size N X and N Y , since mutual information is only relevant to histograms. Finally, mutual information can be derived by (1), (2) and (4) as…”

Section: Vtdfmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Decentralised tracking for human target in multistatic ultra‐wideband radar

Aubry

Chevalier

et al. 2014

IET Radar, Sonar & Navigation

View full text Add to dashboard Cite

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“…In all of these applications the ultra-high resolution of UWB radars is essentially used [28]. UWB radar emissions are at a relatively low frequencytypically between 100 MHz and 3 GHz.…”

Section: Introductionmentioning

confidence: 99%

“…In [5], through-wall UWB radar operating within Federal Communications Commission (FCC) mask was studied for heart beat and breathing rate. In [28][29] [30], UWB radar for detection and positioning of human beings in a complex environment was studied. In the existing works on UWB radar/sensor based target detection, Some algorithms for sensethrough-wall target detection were overviewed in [27], which are mainly based on target response signal strength (1-D) and different copies of signals to construct 2-D features.…”

Section: Introductionmentioning

confidence: 99%

Sense-through-wall human detection based on UWB radar sensors

Liang¹

2016

Signal Processing

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“…IR-UWB technology has many outstanding features such as high range resolution, good penetrability [2] low power consumption and so on. Due to these features, IR-UWB becomes a technology which receives a great deal of attention in many application fields, for example ranging and positioning system [3] [4], human detection [5] [6], vital sign monitoring [7] and so on.…”

Section: Introductionmentioning

confidence: 99%

Algorithm for Gesture Recognition Using an IR-UWB Radar Sensor

Ren¹,

Quan²,

Cho³

2016

JCC

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This paper introduces a human gesture recognition algorithm using an impulse radio ultra-wideband (IR-UWB) radar sensor. Human gesture recognition has been one of the hottest research topics for quite a long time. Many gesture recognition algorithms or systems using other sensors have been proposed such as using cameras, RFID tags and so on. Among which gesture recognition systems using cameras have been extensively studied in past years and widely used in practical. While it might show some deficiencies in some cases. For example, the users might not like to be filmed by cameras considering their privacies. Besides, it might not work well in very dark environments. While RFID tags could be inconvenient to many people and are likely to be lost. Our gesture recognition algorithm uses IR-UWB radar sensor which has pretty high resolution in ranging and adjustable gesture recognition range, meanwhile, does not have problems in privacy issues or darkness. In this paper, the gesture recognition algorithm is based on the moving direction and distance change of the human hand and the change of the frontal surface area of hand towards radar sensor. By combining these changes while doing gestures, the algorithm may recognize basically 6 kinds of hand gestures. The experimental results show that these gestures are of quite good performance. The performance analysis from experiments is also given.

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UWB radar for human being detection

Cited by 119 publications

References 5 publications

Decentralised tracking for human target in multistatic ultra‐wideband radar

Decentralised tracking for human target in multistatic ultra‐wideband radar

Sense-through-wall human detection based on UWB radar sensors

Algorithm for Gesture Recognition Using an IR-UWB Radar Sensor

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