Browsing by Author "Acar, Yunus Emre"

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An Algorithm To Detect the Vital Signs of Multiple Humans in the Presence of High Static Clutters
(SN Bilgi Teknolojileri, 2019) Acar, Yunus Emre; Sarıtaş, İsmail
Human-targeted radar applications have become an important issue in which interest has increased in recent years. In this study, vital signs which are the basis of many human-targeted applications are discussed. In the case of high clutter, which is one of the most important problems of vital sign detection, it is aimed to detect the vital signs of single and multiple human targets. A two-stage algorithm is proposed to detect the single and multiple targets under high static Rayleigh distributed clutter. The ranges of the targets are determined in the first stage of the algorithm while the vital signs are detected in the second stage. The algorithm is developed for Step Frequency Continuous Wave (SFCW) radar structure with I/Q demodulation and tested for different scenarios. The results confirm that the algorithm detects the vital signs accurately.
Citation - Scopus: 1
Comparison of Ml Algorithms To Distinguish Between Human or Human-Like Targets Using the Hog Features of Range-Time and Range-Doppler Images in Through-The Applications
(Scientific and Technological Research Council Turkey, 2022) Acar, Yunus Emre; Saritas, İsmail; Yaldız, Ercan
When detecting the human targets behind walls, false detections occur for many systematic and environmental reasons. Identifying and eliminating these false detections is of great importance for many applications. This study investigates the potential of machine learning (ML) algorithms to distinguish between the human and human-like targets behind walls. For this purpose, a stepped-frequency continuous-wave (SFCW) radar has been set up. Experiments have been carried out with real human targets and moving plates imitating a regular breath of a healthy human. Unlike conventional methods, human and human-like returns are classified using range-Doppler images containing range and Doppler information. Then, the histogram of oriented gradients (HOG) features of the range-Doppler images are extracted, and the number of these features is reduced by principal component analysis (PCA). Finally, popular ML algorithms are executed to distinguish the human and human-like returns. The performances of the ML algorithms are compared for both range-time and range-Doppler images with or without HOG features. Experiments have indicated that the HOG features of the range-Doppler profiles provide the best results with the support vector machine (SVM) classifier with an accuracy of 93.57%.
An Experimental Study: Detecting the Respiration Rates of Multiple Stationary Human Targets by Stepped Frequency Contibuous Wave Radar
(ELSEVIER, 2021) Acar, Yunus Emre; Sarıtaş, İsmail
In this study, it is aimed to improve the maximum range and range resolution while detecting multiple targets’ respiration rates. An original algorithm has been proposed for this purpose, and a Stepped Frequency Continuous Wave radar has been set up for experiments. Experiments have been executed with periodically moving plates and human targets. With a resolution of 30 cm, the detected maximum ranges are 7 m and 6.3 m for moving plate and human targets, respectively. In moving plate experiments, the average accuracies of the frequency measurements are above 98% for both single and multiple-target scenarios. In human target experiments, the average accuracy of the respiration rate measurements is 96.58% for single target experiments while it is 94.44% for multiple targets. The results show that the proposed structure outperforms the state-of-the-art benchmark in terms of the capability of sensing the respiration rate in a wide range with a high resolution.
Citation - WoS: 16
Citation - Scopus: 20
An Experimental Study: Detecting the Respiration Rates of Multiple Stationary Human Targets by Stepped Frequency Continuous Wave Radar
(ELSEVIER SCI LTD, 2021) Acar, Yunus Emre; Sarıtaş, İsmail; Yaldız, Ercan
In this study, it is aimed to improve the maximum range and range resolution while detecting multiple targets' respiration rates. An original algorithm has been proposed for this purpose, and a Stepped Frequency Continuous Wave radar has been set up for experiments. Experiments have been executed with periodically moving plates and human targets. With a resolution of 30 cm, the detected maximum ranges are 7 m and 6.3 m for moving plate and human targets, respectively. In moving plate experiments, the average accuracies of the frequency measurements are above 98% for both single and multiple-target scenarios. In human target experiments, the average accuracy of the respiration rate measurements is 96.58% for single target experiments while it is 94.44% for multiple targets. The results show that the proposed structure outperforms the state-of-the-art benchmark in terms of the capability of sensing the respiration rate in a wide range with a high resolution. (C) 2020 Elsevier Ltd. All rights reserved.
Citation - WoS: 6
Citation - Scopus: 11
An S-Band Zero-If Sfcw Through-The Radar for Range, Respiration Rate, and Doa Estimation
(ELSEVIER SCI LTD, 2021) Acar, Yunus Emre; Sarıtaş, İsmail; Yaldız, Ercan
This study presents a Zero-IF structured Stepped Frequency Continuous Wave (SFCW) radar system for range, respiration rate, and DOA estimation of the targets behind the walls. The radar hardware is a combination of SFCW and Uniform Linear Array (ULA) techniques. Four main improvements are done in signal processing. Averaging Delay Line Cancellation (ADLC) is proposed for moving-target indication. As a post-processing solution to the disruptive effects, a self-acting SVD-based algorithm is offered. The displacement signals of the targets are obtained after applying an additional phase extraction and wavelet-based filtering to lessen the phase discontinuities and noises. The Direction of Arrival (DOA) is estimated over the positive and negative range profiles of two separate antenna pairs. The median of these four angle values is used as the final DOA estimation. The performance of the system is tested with more than 150 experiments and compared with state-of-the-art studies.
Citation - WoS: 10
Citation - Scopus: 13
Small Motion Detection and Non-Contact Vital Signs Monitoring With Continuous Wave Doppler Radars
(KAUNAS UNIV TECHNOLOGY, 2020) Şeflek, İbrahim; Acar, Yunus Emre; Yaldız, Ercan
Radars have become devices that one can come across in any environment at any moment. This means that they enter to all areas of life and even in the field of medicine and will be used more intensively in the future. Especially, the attention has been drawn to that they are suitable for the non contact vital signs monitoring. In this study, two radar structures operating at 24 GHz (Radar 1) and 2.4 GHz (Radar 2) frequencies are used. Radar 1 structure is created on a printed circuit board (PCB), whereas Radar 2 is obtained by combining discrete components. The 8.5 mm movement performed with the aid of a test mechanism is detected by two radars with percentage errors (PEs) of 2.58% and 6.23%, respectively. For the 0.25 Hz vibration frequency, the error is the same for both radars and is 2.4 %. In measurements taken from a healthy human subject, Radar 1 finds a respiration rate with 1.85 % of PE and heart beat rate with 6.17 % of PE. In Radar 2, these values are 2.35 % and 8.24 % respectively. From the measurement results, it is seen that the resolution of Radar 1 is better than that of Radar 2. The results also indicate that small motion detection and vital signs monitoring are carried out successfully.
Citation - WoS: 5
Citation - Scopus: 5
Wavelet Based Denoising of the Simulated Chest Wall Motion Detected by Sfcw Radar
(LGEP-SUPELEC, 2019) Acar, Yunus Emre; Şeflek, İbrahim; Yaldız, Ercan
Low power and compact radars have emerged with the development of electronic technology. This has enabled the use of radars in indoor environments and the realization of many applications. The detection, tracking and classification of human movements by radar are among the remarkable applications. Contactless detection of human vital signs improves the quality of life of patients being kept under observation and facilitates the work of experts. In this study, it was simulated that the movement of the chest wall was modeled and detected by the SFCW radar. Gaussian, Rician and uniformly distributed random noise types were added to the modeled chest motion at different levels. The noisy signal obtained at the receiver is denoised with different mother wavelet functions and the performances of these functions are presented comparatively.