Short-Time State-Space Method for Micro-Doppler Identification of Walking Subject Using UWB Impulse Doppler Radar

Ren, Lingyun; Tran, Nghia; Foroughian, Farnaz; Naishadham, K.; Piou, Jean E.; Kıłıc, Özlem; Fathy, Aly E.

doi:10.1109/tmtt.2018.2829523

Cited by 34 publications

(17 citation statements)

References 46 publications

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“…6(a) shows the simulated model of the gain-enhanced Vivaldi antenna. This antenna is consisted of two parts: (1) an additional strip at the top, which is printed on both sides of The power consumption of the entire front-end system is only 141.7 mW, which can be battery-powered and has long battery life. Fig.6 shows the transceiver test board and measured S-parameter of the gain-enhanced antenna.…”

Section: A System Implementationmentioning

confidence: 99%

“…A STW radar system is intended for mapping building interiors and detecting static and moving objects hidden behind walls and other optically opaque obstacles. It can be used for a wide variety of purposes such as rescue missions, urban warfare, counter terrorism, non-contact medical monitoring, mine detection through ground penetration, and law enforcement [1]- [28]. In particular, during the current COVID-19 pandemic, a patient's vital signs (such as the respiratory rate and the heart rate) are remotely monitored by a bioradar system and displayed on a monitor for the doctor to check the patient in a sterile environment, thereby avoiding the risk of contact with the patient and the consequent risk of infection.…”

Section: Introductionmentioning

confidence: 99%

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Portable Low-Power Fully Digital Radio-Frequency Direct-Transceiving See-Through-Wall Radar

Zhou

Luo

et al. 2020

IEEE Access

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A see-through-wall (STW) radar system based on a direct digital-logic radio-frequency (RF) pulse generator and an equivalent-time direct RF-sampling receiver chipset is proposed. Both the transmitter and the receiver of the radar system are both operated in the digital domain, considerably simplifying the design complexity and the difficulty of signal processing. In terms of data processing, we replace the conventional analog-domain mixing (self-mixing) and digital-domain mixing (self-mixing) modes by taking the absolute value to down convert the signal to the baseband. Thus, the mixer and the local oscillator are removed, which significantly reduces the power consumption while simplifying the signal processing. To verify the effectiveness of the proposed method, a relevant radar chipset was designed in Taiwan Semiconductor Manufacturing Company (TSMC) 65nm process. The prototype radar has a maximum transmission power of 17 dBm and a maximum equivalent sampling rate of 20 GS/s. The detection distance of the STW radar is 8 m with 30.0 cm thick wall, while the respiratory rate of the stationary life is measured through the wall.

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Section: A System Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Portable Low-Power Fully Digital Radio-Frequency Direct-Transceiving See-Through-Wall Radar

Zhou

Luo

et al. 2020

IEEE Access

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“…M p T ≥ , the coefficients of the low frequency sub-band are processed by the average fusion strategy, such as Eqs. (8), (9) and (10).…”

Section: Fusion Algorithm Of Visible and Radar Images Based On Wavelementioning

confidence: 99%

“…The moving radar target detection method based on high-resolution sparse representation is proposed in document [7]. So literature [8] firstly established the framework of Short-Time sparse Time-Frequency Distribution (ST-TFD). So Short-Time Sparse Fourier Transform and Short-Time Sparse Fractional Fourier Transform based radar moving target detection methods are proposed.…”

Section: Introductionmentioning

confidence: 99%

Research on Target Detection Algorithm of Radar and Visible Image Fusion Based on Wavelet Transform

Fan

Cui

et al. 2020

Teh. vjesn.

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The target detection rate of unmanned surface vehicle is low because of waves, fog, background clutter and other environmental factors on the interference. Therefore, the paper studies the target detection algorithm of radar and visible image fusion based on wavelet transform. The visible image is preprocessed to ensure the detection effect. The multi-scale fractal model is used to extract the target features, and the difference between the fractal features of the target and the background is used to detect the target. The radar image is denoised by a combination of median filtering and wavelet transform. The processed visible light and radar image are fused with wavelet transform strategy. The coefficients of the low frequency sub-band are processed by the average fusion strategy. The coefficients of the high frequency sub-band are processed using a strategy with a higher absolute value. The standard deviation, the spatial frequency and the contrast resolution of the image fusion result are compared. The simulation results show that the processed image is better than the unprocessed image after the fusion.

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“…Several researchers have extracted parameters of interest from scattered fields or circuit response using signal processing techniques such as Prony's method [5,6], pencil of functions [7][8][9][10][11], autoregressive moving average (ARMA) [12,13], estimation of signal parameters via rotational invariance techniques (ESPRIT) [14][15][16], multiple signal classification (MUSIC) [17], and the state space method (SSM) [18][19][20][21]. Applications include computation of complex natural resonances and eigenmodes [22][23][24][25][26][27][28], impulse response characterization of time-domain signatures [29][30][31][32][33][34], broadband equivalent circuit parameter extraction [35,36], identification of radar target's features [37][38][39][40], extraction of biomedical vital signs from UWB radar measurements [41][42][43], and location of buried targets using ground penetrating radar [44]. The basis behind such signal processing applications is that the EM field scattered by an object can be adequately represented as a sum of damped sinusoids, whose amplitude and phase are closely related to the physical parameters of interest.…”

Section: Introductionmentioning

confidence: 99%

State Space Modelling of Electromagnetic Responses --- A Practical Approach to Extract Parameters From Simulated or Measured Data

Naishadham¹

2021

PIER B

Self Cite

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As computing power and algorithmic advances have evolved rapidly in the recent past, it is now feasible to solve complex electromagnetic (EM) problems involving scattering, radar cross section, antenna design, microwave circuit design, artificial EM materials, etc., using full-wave numerical methods. Several general-purpose commercial software packages are routinely used in industry in all these domains for EM analysis or design. However, the task of processing large sets of data output from these design studies and analyses is generally beyond the realm of commercial software packages, and the designer spends many hours writing problem-specific computer programs to extract the desired performance parameters. Some examples where auxiliary processing is needed for the extraction of EM parameters of interest include determination of coupling coefficients or the unloaded quality factor of a dielectric resonator, de-embedding feed lines from antenna currents, removal of discontinuity effects, and the extraction of equivalent circuit models. The same considerations as simulated data apply to the parametric analysis of measured data in the presence of noise. This paper presents a versatile datadriven spectral model derived from a state-space system representation of the computed or measured EM fields, from which all the parameters of interest can be extracted. An attractive feature of the state space method is its ability to identify a small number of system transfer function poles uniquely associated with a specific scattering mechanism or modal response, thereby enabling its isolation from the total response for detailed study. For example, using SSM, specular reflection and creeping waves on a smooth convex surface can be analyzed, and the diffraction at the edges can be isolated from the composite RCS of a large body. The desired field parameter is extracted or estimated from synthetic or measured data using a linear system of a relatively small model order that characterizes the specific modal response of interest. Illustrative examples will be presented to demonstrate the usefulness of the proposed approach for parametric extraction.

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Short-Time State-Space Method for Micro-Doppler Identification of Walking Subject Using UWB Impulse Doppler Radar

Cited by 34 publications

References 46 publications

Portable Low-Power Fully Digital Radio-Frequency Direct-Transceiving See-Through-Wall Radar

Portable Low-Power Fully Digital Radio-Frequency Direct-Transceiving See-Through-Wall Radar

Research on Target Detection Algorithm of Radar and Visible Image Fusion Based on Wavelet Transform

State Space Modelling of Electromagnetic Responses --- A Practical Approach to Extract Parameters From Simulated or Measured Data

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