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Through-wall uwb radar based on sparse deconvolution with arctangent regularization for locating human subjects
(2021-04-01)
Rittiplang, Artit
;
Phasukkit, Pattarapong
A common problem in through-wall radar is reflected signals much attenuated by wall and environmental noise. The reflected signal is a convolution product of a wavelet and an unknown object time series. This paper aims to extract the object time series from a noisy receiving signal of through-wall ultrawideband (UWB) radar by sparse deconvolution based on arctangent regulariza-tion. Arctangent regularization is one of the suitably nonconvex regularizations that can provide a reliable solution and more accuracy, compared with convex regularizations. An iterative technique for this deconvolution problem is derived by the majorization–minimization (MM) approach so that the problem can be solved efficiently. In the various experiments, sparse deconvolution with the arctangent regularization can identify human positions from the noisy received signals of through-wall UWB radar. Although the proposed method is an odd concept, the interest of this paper is in applying sparse deconvolution, based on arctangent regularization with an S-band UWB radar, to provide a more accurate detection of a human position behind a concrete wall.
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Deep Learning-Based Human Recognition Through the Wall using UWB radar
(2021-01-01)
Assawaroongsakul, Pongpol
;
Khumdee, Mawin
;
Phasukkit, Pattarapong
;
Houngkamhang, Nongluck
Human activity detection in obscured or invisible area, for instance, human detection through the wall has become an interesting topic because it has potential for security, rescue, activity analysis application, etc. UWB radar, a detection system produces short radio frequency pulses and measures the reflected signals which UWB pulses have high spatial resolution and enable penetration in dielectric materials, was used to collect human activity through the wall signals at the frequency range of 3 GHz in this research. Subsequently, we applied signal data with the Deep Neural Network model to classify 5 classes of human activity including standing, walking, sitting, laying, and no-human gave the F1 score up to 96.94%.
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1-Tx/5-Rx through-wall UWB switched-antenna-array radar for detecting stationary humans
(2020-12-01)
Rittiplang, Artit
;
Phasukkit, Pattarapong
This research proposes a through-wall S-band ultra-wideband (UWB) switched-antenna-array radar scheme for detection of stationary human subjects from respiration. The proposed antenna-array radar consists of one transmitting (Tx) and five receiving antennas (Rx). The Tx and Rx antennas are of Vivaldi type with high antenna gain (10 dBi) and narrow-angle directivity. The S-band frequency (2–4 GHz) is capable of penetrating non-metal solid objects and detecting human respiration behind a solid wall. Under the proposed radar scheme, the reflected signals are algorithmically preprocessed and filtered to remove unwanted signals, and 3D signal array is converted into 2D array using statistical variance. The images are reconstructed using back-projection algorithm prior to Sinc-filtered refinement. To validate the detection performance of the through-wall UWB radar scheme, simulations are carried out and experiments performed with single and multiple real stationary human subjects and a mannequin behind the concrete wall. Although the proposed method is an odd concept, the interest of this paper is applying the 1-Tx/5-Rx UWB switched-antenna array radar with the proposed method that is capable of distinguishing between the human subjects and the mannequin behind the concrete wall.
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Optimal central frequency for non-contact vital sign detection using monocycle uwb radar
(2020-05-02)
Rittiplang, Artit
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Phasukkit, Pattarapong
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Orankitanun, Teerapong
Ultra-wideband (UWB) radar has become a critical remote-sensing tool for non-contact vital sign detection such as emergency rescues, securities, and biomedicines. Theoretically, the magnitude of the received reflected signal is dependent on the central frequency of mono-pulse waveform used as the transmitted signal. The research is based on the hypothesis that the stronger the received reflected signals, the greater the detectability of life signals. In this paper, we derive a new formula to compute the optimal central frequency to obtain as maximum received reflect signal as possible over the frequency up to the lower range of Ka-band. The proposed formula can be applicable in the optimization of hardware for UWB life detection and non-contact monitoring of vital signs. Furthermore, the vital sign detection results obtained by the UWB radar over a range of central frequency have been compared to those of the former continuous (CW) radar to provide additional information regarding the advantages and disadvantages of each radar.
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UWB Radar for Multiple Human Detection Through the Wall Based on Doppler Frequency and Variance Statistic
(2019-11-01)
Rittiplang, Artit
;
Phasukkit, Pattarapong
Multiple human detection through the wall has become an interesting topic for security, rescue, life detecting under earthquake rubble, etc. This paper presents a UWB radar at 3 GHz for detecting multiple humans through the wall based on Doppler frequency and variance statistic of the respiratory signal. Technically, we have referred to efficiently simple methods are FFT and variance statistic for identifying the respiratory frequency of multiple persons quickly. Experimental results show the methods can identify and evaluate quickly respiratory frequencies of two persons through the wood wall.
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IR-UWB generate by FPGA for Non-contact Respiration Measurements
(2019-11-01)
Buasombat, Panupong
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Pungpa, Nonthakorn
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Phasukkit, Pattarapong
Respiration rate detections and measurement has a benefit for elementary symptom in medical application. In present, most of respiration examination in medical field still needs to contact electrode with skin which is main still problem for some patient. Patients who got problem with skin like dermatitis or unable for contact case cause the problem for respiration rate detection. So, this research intends to design non-contact respiration measurement system for resolve this problem. The research applies impulse radio function with ultra-wideband wave (UWB) generate by field programmable gate array (FPGA) for detect respiration rate. In the experiment, we have designed the signal processing algorithm for respiration rate measurement by Fast-Fourier Transform (FFT) of doppler frequency from UWB detection. Result has compared respiration rate measurement between non-contact respiration rate by designed algorithm and standard contact respiration monitoring belt.

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