• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.39-46
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• 2024

In this paper, we propose an efficient method for estimating the number of people and their locations using multiple IR-UWB radar sensors. Using three IR-UWB radar sensors in the indoor space, the measured signal from the target is processed to remove the clutter using rejection methods. Then, to further remove the clutter and to determine the presence of the human, the time-frequency image representing the micro-Doppler is obtained and classified by a convolutional neural network. Finally, the system finds the number of human objects and estimates each position in a two-dimensional space. In experiments using the measured data, the system successfully estimated the location and number of individuals with a high accuracy ≈ 88.68 %.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.5
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• pp.419-425
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• 2017

This paper presents CMOS UWB RFIC based radar system for high speed target detection. The system can achieve resolution of 15 cm and detection range of 15 m. For developed system, single chip CMOS UWB IC is implemented. To reduce the measuring and processing time, envelope detection and equivalent time sampling technique are used. Measurement results show that the bandwidth and center frequency of UWB pulse can be adjusted in the range of 0.5 GHz~1.0 GHz, 3.5 GHz~4.5 GHz, respectively. Signal processing time including scan time over 15 m distance is about $150{\mu}sec$.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.1
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• pp.33-40
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• 2015

The number of people who are suffering from chronic sleep disorder has been growing dramatically in modern era. In order to diagonse the sleep disorder, sleep doctors perform polysomnography: Patients sleep with attaching several vital sign sensors on their body, and doctors monitor the patients in order to find the exact reason of the sleep disorder. Typical polysmonography makes patients sleep with several sensors on their bodies, which prevents the patients from making a comfortable sleep. Furthermore, it is impossible to have a long-term monitoring since the measurements should be done in sleep hosiptal within a few hours. In order to tackle these problems in the typical polysomnography, we envision the development of a non-contact long-term home polysomnography system using UWB radar and related technologies such as multi-modal signal processing.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.25-32
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• 2022

IR-UWB radar has been regarded as the most promising technology for non-contact respiration and heartbeat monitoring because of its ability of detecting slight motion even in submillimeter range. Measuring heart rate is most challenging since the chest movement by heartbeat is quite subtle and easily interfered with by a random body motion or background noise. Additionally, periodic sampling can be limited by the performance of computer that handles the radar signals. In this paper, we deploy Lomb-Scargle periodogram method that estimates heart rate even with irregularly sampled data and uneven signal amplitude. Lomb-Scargle periodogram is known as a method for finding periodicity in irregularly-sampled and noisy data set. We also implement a motion detection scheme in order to make the heart rate estimation pause when a random motion is detected. Our scheme is implemented using Novelda's X4M03 radar development kit and its corresponding drivers and Python packages. Experimental results show that the estimation with Lomb-Scargle periodogram yield more accurate heart rate than the method of measuring peak-to-peak distance.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.10-17
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• 2023

Purpose: In this paper, a distance estimation technique for indoor location estimation using IR-UWB is proposed and researched. We propose an algorithm that can increase the SNR lowered due to clutter or noise in an indoor environment. Method: In order to clutter suppression and detect weak signals, we analyze the existing studies of background remover, correlation, and singular vector decomposition techniques and propose an algorithm. Result: The proposed algorithm, the average error was 0.57m up to 11.5m, and the error were 0.49m from 6m to 11.5m. the average error rate was reduced by about 1m compared to the previous study. Conclusion: It can be used as a technique for detecting weak signals in clutter and noise environments for distance or location estimation, and can also be used as a human life detection technique to reduce damage to people in a disaster situation by using UWB radar which has highly transparent.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.733-734
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• 2017

Ultrasonic, infrared, and CCD cameras are typically used to obtain location information, but the error range is large depending on the surrounding environment. However, IR-UWB can be used for distance and location measurement both indoors and outdoors, Technology. It is possible to determine the existence and distance of an object by emitting a short signal width in units of 1 ns and using a reflected signal and a time delay. It is also possible to measure the exact position within the cm error irrespective of the environmental conditions. Since it processes a large number of reflection signals, we try to measure three-dimensional spatial coordinates by improving the noise by using the mean value of the signal, the band pass filter and the FFT.

• Journal of IKEEE
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• v.25 no.1
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• pp.76-82
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• 2021

In this paper, the compressed sensing basic pursuit denoise algorithm adopted to synthetic aperture radar imaging is investigated to improve the object recognition. From the incomplete data sets for image processing, the compressed sensing algorithm had been integrated to recover the data before the conventional back- projection algorithm was involved to obtain the synthetic aperture radar images. This method can lead to the reduction of measurement events while scanning the objects. An ultra-wideband radar scheme using a stripmap synthetic aperture radar algorithm was utilized to detect objects hidden behind the box. The Ultra-Wideband radar system with 3.1~4.8 GHz broadband and UWB antenna were implemented to transmit and receive signal data of two conductive cylinders located inside the paper box. The results confirmed that the images can be reconstructed by using a 30% randomly selected dataset without noticeable distortion compared to the images generated by full data using the conventional back-projection algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5527-5545
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• 2019

Through-wall ultra-wide band (UWB) radar has been considered as one of the preferred and non-contact technologies for the targets detection owing to the better time resolution and stronger penetration. The high time resolution is a result of a larger of bandwidth of the employed UWB pulses from the radar system, which is a useful tool to separate multiple targets in complex environment. The article emphasised on human subject localization and detection. Human subject usually can be detected via extracting the weak respiratory signals of human subjects remotely. Meanwhile, the range between the detection object and radar is also acquired from the 2D range-frequency matrix. However, it is a challenging task to extract human respiratory signals owing to the low signal to clutter ratio. To improve the feasibility of human respiratory signals detection, a new method is developed via analysing the standard deviation based kurtosis of the collected pulses, which are modulated by human respiratory movements in slow time. The range between radar and the detection target is estimated using joint time-frequency analysis (JTFA) of the analysed characteristics, which provides a novel preliminary signature for life detection. The breathing rates are obtained using the proposed accumulation method in time and frequency domain, respectively. The proposed method is validated and proved numerically and experimentally.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.9
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• pp.59-64
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• 2011

Ultra wideband radars attract considerable attention as a short range automotive radar because of its high range resolution. Radar signal reflected from a target often contains unwanted echoes called as clutter, so the detection of target is difficult due to clutter echoes. Therefore, it is important to investigate the radar detector for better detecting from the reflected signals. In this paper, the optimal detector is obtained for various mean and variance value in log-normal clutter environment. The types of non-coherent detectors used are square law detector, linear detector, and logarithmic detector. The performances of detectors are compared in log normal clutter environment and the suitable detector is determined for automotive short range radar application.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.3
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• pp.433-444
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• 2020

This study proposes a method to improve the sleep stage and efficiency estimation of sleep apnea patients using a UWB (Ultra-Wideband) radar. Motion and respiration extracted from the radar signal were used. Respiratory signal disturbances by motion artifacts and irregular respiration patterns of sleep apnea patients are compensated for in the preprocessing stage. Preprocessing calculates the standard deviation of the respiration signal for a shift window of 15 seconds to estimate thresholds for compensation and applies it to the breathing signal. The method for estimating the sleep stage is based on the difference in amplitude of two kinds of smoothed respirations signals. In smoothing, the window size is set to 10 seconds and 34 seconds, respectively. The estimated feature was processed by the k-nearest neighbor classifier and the feature filtering model to discriminate between the sleep periods of the rapid eye movement (REM) and non-rapid eye movement (NREM). The feature filtering model reflects the characteristics of the REM sleep that occur continuously and the characteristics that mainly occur in the latter part of this stage. The sleep efficiency is estimated by using the sleep onset time and motion events. Sleep onset time uses estimated features from the gradient changes of the breathing signal. A motion event was applied based on the estimated energy change in the UWB signal. Sleep efficiency and sleep stage accuracy were assessed with polysomnography. The average sleep efficiency and sleep stage accuracy were estimated respectively to be about 96.3% and 88.8% in 18 sleep apnea subjects.