A novel time of arrival estimation algorithm using an energy detector receiver in MMW systems

Liang, Xiaolin; Zhang, Hao; Lyu, Tingting; Han, Xiao; Gulliver, T. Aaron

doi:10.1186/s13634-017-0520-x

Cited by 10 publications

(4 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this section, a frequency estimation method is given which is based on statistical features of the UAV signals. These features include skewness [58], kurtosis [59], and standard deviation [60]. The goal is to detect the presence of a UAV in a given surveillance area.…”

Section: Proposed Methodsmentioning

confidence: 99%

An Improved Unauthorized Unmanned Aerial Vehicle Detection Algorithm Using Radiofrequency-Based Statistical Fingerprint Analysis

Yang

Qin

Liang³

et al. 2019

Sensors

Self Cite

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) are now readily available worldwide and users can easily fly them remotely using smart controllers. This has created the problem of keeping unauthorized UAVs away from private or sensitive areas where they can be a personal or public threat. This paper proposes an improved radio frequency (RF)-based method to detect UAVs. The clutter (interference) is eliminated using a background filtering method. Then singular value decomposition (SVD) and average filtering are used to reduce the noise and improve the signal to noise ratio (SNR). Spectrum accumulation (SA) and statistical fingerprint analysis (SFA) are employed to provide two frequency estimates. These estimates are used to determine if a UAV is present in the detection environment. The data size is reduced using a region of interest (ROI), and this improves the system efficiency and improves azimuth estimation accuracy. Detection results are obtained using real UAV RF signals obtained experimentally which show that the proposed method is more effective than other well-known detection algorithms. The recognition rate with this method is close to 100% within a distance of 2.4 km and greater than 90% within a distance of 3 km. Further, multiple UAVs can be detected accurately using the proposed method.

show abstract

Section: Proposed Methodsmentioning

confidence: 99%

An Improved Unauthorized Unmanned Aerial Vehicle Detection Algorithm Using Radiofrequency-Based Statistical Fingerprint Analysis

Yang

Qin

Liang³

et al. 2019

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…SVD is applied on (2) [31], which is given by

bold-italicD = U S V^{T},

where S stands for the diagonal matrix, U M × M and V N × N for the two different unitary matrices.…”

Section: Proposed Algorithmmentioning

confidence: 99%

Improved radiation detection algorithm using wavelet packet decomposition

Liang¹,

Deng²,

Zhang³

et al. 2020

IET Radar, Sonar & Navigation

Self Cite

View full text Add to dashboard Cite

“…1) Let v = 0, which is used to indicate the vth IMF; 2) To acquire all these local maximum and minimum values of (20); 3) To get the envelopes including the upper envelope r u (t) and the lower envelope r l (t)of (20) based on the values from 2) by employing the cubic spline function; 4) To generate the average envelope from 3), which can be given by [48]:…”

Section: Frequency Estimatementioning

confidence: 99%

`Through-wall human being detection using UWB impulse radar

Liang

Zhang

et al. 2018

J Wireless Com Network

Self Cite

View full text Add to dashboard Cite

Ultra-wideband (UWB) impulse radar plays an important role in contactless vital sign (VS) detection. The VS can be extracted remotely by acquiring the oscillations in the human chest. Unfortunately, it is usually challenging to identify VS due to the low signal-to-noise ratio (SNR) only based on the traditional fast Fourier transform (FFT) especially in complicated conditions. To extract VS accurately, this paper presents a new scheme by analyzing the skewness characteristic of the received UWB impulses, which are modulated by life activities. The distance from the human subject to the radar antenna can be calculated by performing the discrete short-time Fourier transform (DSFT) on skewness. The frequency of human respiratory movement can be estimated based on the developed ensemble empirical mode decomposition (EEMD)-based accumulation technique by canceling out the harmonics effectively. The performance of the developed detection method is tested with several experiments carried out in different environments.

show abstract

A novel time of arrival estimation algorithm using an energy detector receiver in MMW systems

Cited by 10 publications

References 30 publications

An Improved Unauthorized Unmanned Aerial Vehicle Detection Algorithm Using Radiofrequency-Based Statistical Fingerprint Analysis

An Improved Unauthorized Unmanned Aerial Vehicle Detection Algorithm Using Radiofrequency-Based Statistical Fingerprint Analysis

Improved radiation detection algorithm using wavelet packet decomposition

`Through-wall human being detection using UWB impulse radar

Contact Info

Product

Resources

About