Model-based sub-Nyquist sampling and reconstruction technique for ultra-wideband (UWB) radar

2010 ◽  
Author(s):  
Lam Nguyen ◽  
Trac D. Tran
Keyword(s):  
Ultra Wideband ◽  
Reconstruction Technique ◽  
Model Based ◽  
Uwb Radar ◽  
Sampling And Reconstruction

scholarly journals Investigation of 3D ultra-wideband bandpass filter model based on microstrip multimode resonators

2021 ◽  
Vol 1745 (1) ◽  
pp. 012064
Author(s):  
B A Belyaev ◽  
S A Khodenkov ◽  
N A Shepeta ◽  
A M Popov
Keyword(s):  
Bandpass Filter ◽  
Ultra Wideband ◽  
Filter Model ◽  
Model Based

scholarly journals A Novel Method for Breath Detection via Stepped-Frequency Continuous Wave Ultra-Wideband (SFCW UWB) Radars Based on Operational Bandwidth Segmentation

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3873 ◽  
Author(s):  
Hao Lv ◽  
Teng Jiao ◽  
Yang Zhang ◽  
Fulai Liang ◽  
Fugui Qi ◽  
...  
Keyword(s):  
Continuous Wave ◽  
Doppler Radar ◽  
Ultra Wideband ◽  
Time Dimension ◽  
Processing Scheme ◽  
Practical Applications ◽  
Uwb Radar ◽  
Operational Frequency ◽  
Stepped Frequency ◽  
Breath Detection

Human being detection via ultra-wideband (UWB) radars has shown great prospects in many areas, such as biomedicine, military operation, public security, emergency rescue, and so on. When a person stays stationary, the main feature that separates him/her from surroundings is the movement of chest wall due to breath. There have been many algorithms developed for breath detection while using UWB radars. However, those algorithms were almost based on a basic scheme that focused on processing in the time dimension of UWB data. They did not utilize the benefits from the wide operational bandwidth of UWB radars to show potential superiority over those narrowband systems such as a continuous wave (CW) Doppler radar. In this paper, a breath detection method was proposed based on operational bandwidth segmentation. A basic theoretical model was firstly introduced, indicating that characteristics of breath signals contained in UWB echoes were consistent among the operational frequencies, while those of clutters were not. So, the method divided a set of UWB echo data into a number of subsets, each of which corresponded to a sub-band within the operational bandwidth of the UWB radar. Thus information about the operational frequency is provided for subsequent processing. With the aid of the information, a breath enhancement algorithm was developed mainly by averaging the segmented UWB data along the operational frequency. The algorithm’s performance was verified by data measured by a stepped-frequency CW (SFCW) UWB radar. The experimental results showed that the algorithm performed better than that without the segmentation. They also showed its feasibility for fast detection of breath based on a short duration of data. Moreover, the method’s potential for target identification and impulse-radio (IR) UWB radar was investigated. In summary, the method provides a new processing scheme for UWB radars when they are used for breath detection. With this scheme, the UWB radars have a benefit of greater flexibility in data processing over those narrowband radars, and thus will perform more effectively and efficiently in practical applications.

scholarly journals A Multiple Target Positioning and Tracking System Behind Brick-Concrete Walls Using Multiple Monostatic IR-UWB Radars

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4033 ◽  
Author(s):  
Yoo ◽  
Wang ◽  
Seol ◽  
Lee ◽  
Chung ◽  
...  
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Detection Rate ◽  
Tracking System ◽  
Radar System ◽  
Ultra Wideband ◽  
Radar Signal ◽  
High Detection Rate ◽  
Concrete Walls ◽  
Uwb Radar

Recognizing and tracking the targets located behind walls through impulse radio ultra-wideband (IR-UWB) radar provides a significant advantage, as the characteristics of the IR-UWB radar signal enable it to penetrate obstacles. In this study, we design a through-wall radar system to estimate and track multiple targets behind a wall. The radar signal received through the wall experiences distortion, such as attenuation and delay, and the characteristics of the wall are estimated to compensate the distance error. In addition, unlike general cases, it is difficult to maintain a high detection rate and low false alarm rate in this through-wall radar application due to the attenuation and distortion caused by the wall. In particular, the generally used delay-and-sum algorithm is significantly affected by the motion of targets and distortion caused by the wall, rendering it difficult to obtain a good performance. Thus, we propose a novel method, which calculates the likelihood that a target exists in a certain location through a detection process. Unlike the delay-and-sum algorithm, this method does not use the radar signal directly. Simulations and experiments are conducted in different cases to show the validity of our through-wall radar system. The results obtained by using the proposed algorithm as well as delay-and-sum and trilateration are compared in terms of the detection rate, false alarm rate, and positioning error.

scholarly journals Robotic control for cognitive UWB radar

2018 ◽  
Vol 02 (01) ◽  
pp. 1850009
Author(s):  
Stefan Brüggenwirth ◽  
Fernando Rial
Keyword(s):  
Communication Systems ◽  
Sliding Mode ◽  
Wide Spectrum ◽  
Observation Time ◽  
Ultra Wideband ◽  
Limiting Factor ◽  
Planning Problem ◽  
Uwb Radar ◽  
Manipulator Arm ◽  
Six Dof

In the paper, we describe a trajectory planning problem for a six-DoF robotic manipulator arm that carries an ultra-wideband (UWB) radar sensor with synthetic aperture (SAR). The resolution depends on the trajectory and velocity profile of the sensor head. The constraints can be modeled as an optimization problem to obtain a feasible, collision-free target trajectory of the end-effector of the manipulator arm in Cartesian coordinates that minimizes observation time. For 3D reconstruction, the target is observed in multiple height slices. For through-the-wall radar the sensor can be operated in sliding mode for scanning larger areas. For IED inspection the spotlight mode is preferred, constantly pointing the antennas towards the target to obtain maximum azimuth resolution. UWB sensors typically use a wide spectrum shared by other RF communication systems. This may become a limiting factor on system sensitivity and severely degrade the image quality. Cognitive radars can adapt dynamically their bandwidth, frequency and other transmit parameters to the radio frequency environment to avoid interference with primary users.

scholarly journals A Novel, Portable and Fast Moisture Content Measuring Method for Grains Based on an Ultra-Wideband (UWB) Radar Module and the Mode Matching Method

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4224 ◽  
Author(s):  
Chi Zhang ◽  
Zhichao Shi ◽  
Haiying Yang ◽  
Xiaoguang Zhou ◽  
Zidan Wu ◽  
...  
Keyword(s):  
Reflection Coefficient ◽  
Moisture Content ◽  
Complex Permittivity ◽  
Ultra Wideband ◽  
Mode Matching ◽  
Matching Method ◽  
Mode Matching Method ◽  
Isolation Layer ◽  
Uwb Radar ◽  
Rough Rice

To perform fast and portable grain moisture measurements under field conditions, a novel moisture sensor was designed, which consisted of a coaxial waveguide, a circular waveguide, and an isolation layer. The electromagnetic characteristics of the sensor were simulated and measured. The analytical model, which represented the relationship between the reflection coefficient of the sensor and the complex permittivity of grain, was established by using the mode matching method. The reflection coefficient of the sensor was measured by using an ultra-wideband (UWB) radar module, and the moisture content of grains was calculated from the complex permittivity by using density-independent model. To verify the performance of the proposed method, wheat, rough rice, and barley were taken as examples. The measured results in the range from 1.0% to 26.0%, wet basis, agreed well with the reference values (R2 was more than 0.99), and the maximum absolute errors for wheat, rough rice, and barley were 1.1%, 1.0%, and 1.4%, respectively. In addition, the effect of isolation layer was discussed. Both the simulation results and the experimental results showed that the isolation layer improved the stability of sensor.

A model-based reconstruction technique for quantitative myocardial perfusion imaging

2015 ◽  
Vol 76 (3) ◽  
pp. 880-887 ◽  
Author(s):  
Johannes Tran-Gia ◽  
David Lohr ◽  
Andreas Max Weng ◽  
Christian Oliver Ritter ◽  
Daniel Stäb ◽  
...  
Keyword(s):  
Myocardial Perfusion Imaging ◽  
Myocardial Perfusion ◽  
Perfusion Imaging ◽  
Reconstruction Technique ◽  
Model Based ◽  
Quantitative Myocardial Perfusion

scholarly journals Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5503
Author(s):  
Xinyue Zhang ◽  
Xiuzhu Yang ◽  
Yi Ding ◽  
Yili Wang ◽  
Jialin Zhou ◽  
...  
Keyword(s):  
Physical Activity ◽  
Vital Signs ◽  
Motion Artifacts ◽  
Body Motion ◽  
Ultra Wideband ◽  
Body Movements ◽  
Range Resolution ◽  
Vital Signs Monitoring ◽  
Uwb Radar ◽  
Empirical Wavelet Transform

Vital signs monitoring in physical activity (PA) is of great significance in daily healthcare. Impulse Radio Ultra-WideBand (IR-UWB) radar provides a contactless vital signs detection approach with advantages in range resolution and penetration. Several researches have verified the feasibility of IR-UWB radar monitoring when the target keeps still. However, various body movements are induced by PA, which lead to severe signal distortion and interfere vital signs extraction. To address this challenge, a novel joint chest–abdomen cardiopulmonary signal estimation approach is proposed to detect breath and heartbeat simultaneously using IR-UWB radars. The movements of target chest and abdomen are detected by two IR-UWB radars, respectively. Considering the signal overlapping of vital signs and body motion artifacts, Empirical Wavelet Transform (EWT) is applied on received radar signals to remove clutter and mitigate movement interference. Moreover, improved EWT with frequency segmentation refinement is applied on each radar to decompose vital signals of target chest and abdomen to vital sign-related sub-signals, respectively. After that, based on the thoracoabdominal movement correlation, cross-correlation functions are calculated among chest and abdomen sub-signals to estimate breath and heartbeat. The experiments are conducted under three kinds of PA situations and two general body movements, the results of which indicate the effectiveness and superiority of the proposed approach.

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