Using Wavelet Entropy to Distinguish Between Humans and Dogs Detected by Uwb Radar

Wang, Yan; Yu, Xiao; Zhang, Yang; Lv, Hao; Jiao, Teng; Lu, Guo; Li, Wen Zhe; Zhao, Li; Jing, Xi Jing; Jing, Wang

doi:10.2528/pier13032508

Cited by 20 publications

(20 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[7]) and wavelet transformation and wavelet entropy (e.g. [14]) can be rated among them. The fundamentals of Hilbert-Huang transformation, S-transform, and MUSIC methods can be found in Refs.…”

Section: Static Person Detection and Localization: State-of-the Artmentioning

confidence: 99%

Multiple Person Localization Based on Their Vital Sign Detection Using UWB Sensor

Novák¹,

Švecová²,

Kocur³

2017

Microwave Systems and Applications

View full text Add to dashboard Cite

In the past period, great efforts have been made to develop methods for through an obstacle detection of human vital signs such as breathing or heart beating. For that purpose, ultra-wideband (UWB) radars operating in the frequency band DC-5 GHz can be used as a proper tool. The basic principle of respiratory motion detection consists in the identification of radar signal components possessing a significant power in the frequency band 0.2-0.7 Hz (frequency band of human respiratory rate) corresponding to a constant bistatic range between the target and radar. To tackle the task of detecting respiratory motion, a variety of methods have been developed. However, the problem of person localization based on his or her respiratory motion detection has not been studied deeply. In order to fill this gap, an approach for multiple person localization based on the detection of their respiratory motion will be introduced in this chapter.

show abstract

Section: Static Person Detection and Localization: State-of-the Artmentioning

confidence: 99%

Multiple Person Localization Based on Their Vital Sign Detection Using UWB Sensor

Novák¹,

Švecová²,

Kocur³

2017

Microwave Systems and Applications

View full text Add to dashboard Cite

show abstract

“…More signal components indicate a more complex and irregular signal, and a larger value of wavelet entropy. Generally, dog signals are more complex than human signals [12,22]. Therefore, the MWE of human targets is much smaller than that of dog targets.…”

mentioning

confidence: 99%

“…where a is the scaling parameter which measures the degree of compression, b is the translation parameter which determines the time location of the wavelet, and t represents time. Let L 2 ( ) be the real square integrable function space, the discrete wavelet transform of a signal S(t) ∈ L 2 ( ) is defined as [12,13]:…”

mentioning

confidence: 99%

See 1 more Smart Citation

An Accurate Method to Distinguish Between Stationary Human and Dog Targets Under Through-Wall Condition Using UWB Radar

Liang

Wang

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

Research work on distinguishing humans from animals can help provide priority orders and optimize the distribution of resources in earthquake- or mining-related rescue missions. However, the existing solutions are few and their stability and accuracy of classification are less. This study proposes an accurate method for distinguishing stationary human targets from dog targets under through-wall condition based on ultra-wideband (UWB) radar. Eight humans and five beagles were used to collect 130 samples of through-wall signals using the UWB radar. Twelve corresponding features belonging to four categories were combined using the support vector machine (SVM) method. A recursive feature elimination (RFE) method determined an optimal feature subset from the twelve features to overcome overfitting and poor generalization. The results after ten-fold cross-validation showed that the area under the receiver operator characteristic (ROC) curve can reach 0.9993, which indicates that the two subjects can be distinguished under through-wall condition. The study also compared the ability of the proposed features of four categories when used independently in a classifier. Comparison results indicated that wavelet entropy-corresponding features among them have the best performance. The method and results are envisioned to be applied in various practical situations, such as post-disaster searching, hostage rescues, and intelligent homecare.

show abstract

“…This topic is of great concern since UWB technology in combination with MIMO systems finds more and more applications in areas such as location tracking for outdoor emergency services [4,5], location tracking and sensor for mobile outdoor users [6], medical [7] and electronic warfare applications [3]. Moreover, some research results [8][9][10] proved that a joint radar and wireless communication system would constitute a unique platform for future intelligent environmental sensing and ad-hoc communication networks, in terms of both spectrum efficiency and cost effectiveness.…”

Section: Introductionmentioning

confidence: 99%

Effects of Non-Fixed Scatterers' Random Movements on Ultra-Wideband Miso Channels

Pistea¹

2014

PIER C

View full text Add to dashboard Cite

Abstract-Most wireless channel models assume fixed scatterers with specific geometrical distributions in the propagation environment. In reality most scatterers move with random movements on the azimuth plane. In this paper, the effects of such scatterers' random movements on the cross-correlation function (CCF) of wideband (WB) and ultra-wideband (UWB) non-isotropic multiple-input multiple-output (MIMO) channels are characterized. The CCF of WB/UWB MIMO channels is calculated not by assuming a specific geometry for scatterers in space but based on specific mathematical relationships between physical parameters of the wireless channel along with appropriate assumptions on their probability density functions (pdfs). The CCF is used to determine the influence of moving scatterers, in a stationary scenario, on the power spectral density (PSD) and the coherence time of WB and UWB multiple-input single-output (MISO) channels, as a particular case of MIMO channels. Unlike the fixed scatterers case, the PSD is not a band-limited process, it decays with frequency.

show abstract

Using Wavelet Entropy to Distinguish Between Humans and Dogs Detected by Uwb Radar

Cited by 20 publications

References 30 publications

Multiple Person Localization Based on Their Vital Sign Detection Using UWB Sensor

Multiple Person Localization Based on Their Vital Sign Detection Using UWB Sensor

An Accurate Method to Distinguish Between Stationary Human and Dog Targets Under Through-Wall Condition Using UWB Radar

Effects of Non-Fixed Scatterers' Random Movements on Ultra-Wideband Miso Channels

Contact Info

Product

Resources

About