UWB Radar Sensor Networks for Sense-Through-Foliage Target Detection

Liang, Qilian; Samn, Sherwood; Cheng, Xiuzhen

doi:10.1109/icc.2008.425

Cited by 25 publications

(6 citation statements)

References 3 publications

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“…Using the data samples in the training sets (400 samples for each scenario, 200 samples for each target), we learned dictionaries (1) (2) ,…”

Section: B Experimental Resultsmentioning

confidence: 99%

“…They can detect targets through obstacles such as foliage. There have been many efforts undertaken to investigate sense through foliage target detection and classification based on UWB radar, such as radar sensor network (RSN) [1,2], short-time Fourier transform (STFT) [3] approach and differential based approach [4]. These studies focused on the detection of target but not on the recognition of target types.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Sense-through-Foliage Target Recognition Method Based on Sparse Representation

Zhai

Jiang

Huang

2013

MILCOM 2013 - 2013 IEEE Military Communications Conference

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In this paper, a novel sparse representation (SR) based method for recognizing targets under different foliage scenarios is presented. Target echo signals of different targets in different scenarios measured by bistatic ultra-wideband (UWB) radar are used for scenarios and targets recognition. Particularly, two overcomplete dictionaries one for scenarios and one for targets are learned from measured real target echo signal waveforms via dictionary learning technique. The SR expresses an input signal as the linear combination of a small number of the learned dictionary elements, which are from the same category as the input signal. The SR of a test target echo signal can be achieved by solving an L 0 -norm minimization problem. For targets recognition under multi-scenario, firstly, we locate the scenario of the targets with the overcomplete dictionary for scenarios via SR. Then, the types of the targets are recognized using the overcomplete dictionary for targets via SR. The effectiveness of the proposed approach is verified by experiments taken in the forest measurement. Experimental results on real measured data show that the proposed method achieves higher recognition accuracy.

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“…Using the data samples in the training sets (400 samples for each scenario, 200 samples for each target), we learned dictionaries (1) (2) ,…”

Section: B Experimental Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Sense-through-Foliage Target Recognition Method Based on Sparse Representation

Zhai

Jiang

Huang

2013

MILCOM 2013 - 2013 IEEE Military Communications Conference

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“…Figure 11(c) shows the transmission factor in the small intestine, by using an input internal and a load impedance of Z S = 2.93 + j2407. 9 and Z L = 20.12+j455.28 , a high value of −23.89 dB can be obtained at 500 MHz. If Z S and Z L are not changed, for example, using constant value of Z S = 3.10 + j2405.78 and Z L = 20.46 + j452.43 , values of −27.88 dB and −29.98 dB are obtained in the cases of the large intestine and the small intestine, respectively.…”

Section: Transmission Characteristics Depend On Organs and Impedance Matchingmentioning

confidence: 92%

Study on the Electromagnetic Field Distribution of an Implantable Antenna for an Intelligent Health Monitoring System

Li¹,

Duan²,

Yang³

et al. 2019

IEEE Access

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In this paper, an intelligent health monitoring system based on body-centric wireless communications is studied, and the implantable antenna is investigated. To design the antennas for intelligent health monitoring systems, the electromagnetic near-field distribution of an implantable antenna placed in the alimentary canal of a human body is investigated by a numerical analysis. The electronic field distribution and the transmission factor of an implantable antenna placed in different parts of the human alimentary canal are presented and compared. It is found that the electronic field distribution of the implantable antenna depends on the operating frequency of the antenna and the conductivity distribution of the human body. The transmission characteristics of the electromagnetic wave from the implantable antenna to the outside depending on the frequency, distance, and filling materials of the alimentary canal. The impedance matching of the implantable antenna in different organs is also presented and compared.INDEX TERMS Intelligent body healthcare management, implantable antenna, near-field distribution, transmission characteristic, impedance matching.

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“…Using time of arrival (ToA) methods several researchers have reported estimation errors of less than 5 cm in a variety of outdoor and indoor environments (Falsi et al, 2006). UWB signals have been proposed for the detection of vegetation, which can be very useful for outdoor navigation (Liang et al, 2008), and of people behind walls (Zetik et al, 2006) which can be useful in rescue missions. It is then expected that in many applications mobile robots will be equipped with UWB transceivers.…”

Section: Wireless Localizationmentioning

confidence: 99%