건국대학교 밀리미터파 집적시스템 연구실
밀리미터파 집적시스템 연구실에서는 아날로그, RF, 초고주파에 이르는 다양한 주파수 대역 IC기술과 전자기파 특성기반 다양한 응용 시스템 연구를 수행합니다. 모든 분들의 방문을 환영합니다.
위치: 공학관 321-1호 (교수 연구실), 신공학관 1117호 (학생 연구실), KU기술혁신관 501호 (교원 창업기업)
OUR LATEST RESEARCHES
A D-band Two-Way Differential Power Divider on 65-nm CMOS Process
A CMOS two-way differential power divider is proposed to reduce the insertion loss (IL) and size in the D-band. The power distribution is achieved using a low-loss differential power divider with a capacitive loading structure, without modifying the matching network of the unit devices. In addition, the degradation of the IL due to the parasitic inductance of groundings is made negligible by using the virtual ground of the differential structure. The impedance of the differential-mode transmission line (TL), which is half that of the single-ended line, is designed in the impedance range achievable in the bulk CMOS process, utilizing capacitive loading techniques. The 3-D electromagnetic (EM) simulation results of a two-way power divider show a low IL within 0.35 dB at 110–170 GHz. The proposed power divider achieves a measured minimum IL of 0.32 dB at 160 GHz with a core size of 0.0075 mm2.
Remote Vital Signal Detection Using Ambient Noise Cancellation Based on Beam-Switching Doppler Radar
The remote vital signal detection using the Doppler radar is proposed to reduce the measurement errors caused by environmental factors, including the subject’s body movements. The proposed method for remote detection is based on the radar with beam control, which allows for adjusting the antenna’s radiating direction through spatial synthesis of an antenna array. By altering the beam direction, the proposed radar distinguishes between vital signals (respiration and heartbeat) originating from the asymmetrical movements of the human lungs and heart and the noise signals introduced by environmental factors, such as stationary clutters and the subject’s body movements. The respiration and heartbeat are extracted from the raw radar data obtained from each direction with signal processing techniques, including dc offset removal and random movement cancellation, which are based on the relationship of Bessel functions. An additional algorithm for extracting the correlated data from the acquired vital signals and filtering sudden variations significantly enhances the detection accuracy in the proposed method. In a practical test scenario, the vital signs of a subject walking at 2 km/h on a treadmill were measured in the surroundings with stationary clutters using the proposed method with a beam-switching 5.8-GHz radar module at a distance of 1 m. The measurement results demonstrated error rates of less than 3 beats per minute (bpm) for respiration and 4.2 bpm for heartbeat, compared with reference values obtained from contact-type sensors.