The presence of an obstacle in detecting respiration vital signs using a radar system does not only exhibit attenuation and phase shift effects on the radar signal but also causes additional beat frequencies to appear beside those from the target. When a conventional FMCW radar system detects the peak of the received signal spectrum as a beat frequency, this will give an error of detection. The respiratory vital signs will then be undetectable. A method to overcome this obstacle problem is needed. Therefore the implementation of the FMCW radar system in detecting respiratory vital signs behind the wall can be realized. In this paper, a method to deal with the previously mentioned problem is proposed. The proposed method consists of a method for identifying the obstacle response. Then the results are used to eliminate the beat frequency that arises from the obstacle structure, and therefore the signal to clutter ratio (SCR) can be improved. Furthermore, the method is combined with the phase detection method, which is applied to extract the Doppler response related to the target respiratory vital signs. The weighting process by elaborating cross correlation is also employed for minimizing clutter from other objects reflection under debris. A laboratory experiment by developing an FMCW radar system with a 24 GHz frequency operation was performed in this research. The proposed detection method was elaborated in the post-processing of the radar system. The experiment result demonstrates that the proposed method is capable of eliminating the effect of the wall and successfully extracting the respiration vital sign pattern.

The displacement on the bridge structure is an essential parameter in identifying the bridge structure’s health. The non-contact measurement method is preferable in practice, and the radar system is potentially employed for developing displacement measurement technology. Frequency Modulated Continuous Wave (FMCW) radar has a feature for detecting the target location. However, estimating the small displacement in the bridge structure requires extensive bandwidth to reach the proper resolution. The problem of obtaining the required resolution, and adopting the decrease in accuracy due to several possible radar placements during measurement are addressed in this paper. The concept of bridge displacement measurement using a modified FMCW radar system is proposed. Phase information extraction is employed to reach the displacement detection resolution, and the radar elevation detection based on an inclinometer is equipped in the proposed radar system. The simulation and laboratory experiments were conducted by implementing the proposed radar system for detecting the displacement in the bridge model. The experiment results confirm that the proposed FMCW radar was able to estimate the bridge displacement and overcome the decreasing accuracy due to the radar elevation. The multi-point detection technique is also developed in the proposed radar and capable to capture the displacement profile over bridge span. The proposed FMCW system is then recommended as a radar system in developing a non-contact method for bridge displacement measurement and monitoring.

The development of a radar system for human respiration noncontact sensor will contribute to the healthcare field, particularly in the monitoring of patients’ respiration for a long period with all the while providing more advantages, such as hygiene and comfort. The radar system must be able to detect the small displacement with millimeters or centimeters scale on the human body associated with the respiratory activity. The minimum power of electromagnetic wave radiation is also needed to avoid unsafe usability in patients’ respiration monitoring. To attain low power operation and efficient frequency spectrum usage, the multifrequency continuous-wave (MFCW) radar system is proposed in this article as a noncontact sensor for human respiration. The simulation study and laboratory experiment of the MFCW radar system in detecting human respiration were performed, and the comparison study with frequency-modulated continuous-wave (FMCW) radar was discussed in this article. The simulation shows that the effective isotropic radiation power (EIRP) of MFCW is 9 dBm lower than FMCW at a 2-m measurement distance. The result also demonstrates that the proposed MFCW performs well under amplitude and phase noise. The laboratory experiments were conducted by implementing the proposed system using the software-defined radio device. The experiment results also confirm that the proposed MFCW was able to reduce the EIRP and spectrum occupation compared to the FMCW. The MFCW system is then recommended as a radar system in developing a noncontact sensor for respiration monitoring in healthcare.

Radar–drone system is potentially implemented as a method for collecting the soil water content of a large area. Vegetation that may covers the soil surface affects the detection results of soil water content using radar system in plantation areas. Vegetation will influence the propagation mechanism of radar waves, therefore, a method to overcome this effect is needed. The method to compensate the effect of vegetation based on a transmission line model is then proposed in this paper. The transmission line model is used as the concept for transforming the measured reflection coefficient under the vegetation effect to the ground reflection coefficient value. Experiments were carried out by taking a case studies on tea plantations. The tea plant becomes a vegetation layer which its effect needs to be considered on the detection of soil water content. An ultra-wideband radar system with a frequency range of 500 MHz - 3 GHz is proposed in this study. The radar is integrated to hexacopter drone for scanning the tea plantation areas. The radar-drone system flight with a constant elevation from ground level. The experimental results show that the proposed method is able to improve the detection results of soil water content using radar with an accuracy of 96%. The radar-drone performance in detecting soil water content is suitable for precision farming purposes.

Contactless Human to Machine Interface (HMI) is an indispensable technology for handling the machine or equipment in a pandemic situation where the virus can spread through direct contact. The contactless hand gesture sensor is an essential part needed for the HMI system as previously mentioned. Several hand gestures with a similar Doppler response will become problems in applying Doppler radar as a hand gesture sensor that requires a more complex recognition method. This paper proposes spatial diversity implementation for obtaining more accurate hand gesture features to cope with this problem. Array radar was selected as a sensor configuration to create the spatial diversity feature. In this paper, an array configuration of four Continuous Wave (CW) radars is proposed as a contactless sensor for hand gestures. Peak detection based on cross-correlation was employed to determine the time position of the hand gesture Doppler response detected by each CW radar. The time position pattern then becomes a feature of each hand gesture used. The CW radar array is realized with an operating frequency of 10 GHz by using the HB 100 as a CW radar component. The experimental results show that the proposed method can distinguish the hand gesture feature with an accuracy of 96.6 % at a sensing distance of 50 cm. It can differentiate the hand gesture pairs that have the opposite direction movement with a similar Doppler effect, and also requires simple data processing for recognizing different hand gestures.

Small displacement detection capability becomes an important key for developing non-contact sensor for human respiration based on radar system. Frequency modulated continuous wave (FMCW) radar has been widely studied and applied for many applications. With respect to the conventional perspective, large bandwidth is needed for detecting the small displacement related to the human respiration. Meanwhile, extracting the respiration pattern from Doppler response has a drawback in identifying the small displacement location. In this paper, the modification on FMCW system was proposed for obtaining the capability in detecting the human respiration and its distance from the radar. Detecting the phase value of the low pass filter (LPF), output from conventional FMCW was investigated and applied as a modification concept. The pattern, rate and amplitude of respiration are extracted from phase detector output. Beat frequency detection is still elaborated for synthesising the reference signal for phase detection. The result shows that the modified FMCW system proposed the capability of detecting the rate and amplitude respiration and location of the target.