scholarly journals A High Signal–Noise Ratio UWB Radar for Buried Pipe Location Using Golay Complementary Sequences

2019 ◽  
Vol 9 (23) ◽  
pp. 5090 ◽  
Author(s):  
Jingxia Li ◽  
Yang Liu ◽  
Hang Xu ◽  
Bingjie Wang ◽  
Li Liu ◽  
...  

A Golay-based ultra wideband ground penetrating for underground pipes location is proposed and experimentally demonstrated. Golay complementary codes with the code length of 1024 and frequency of 1 GHz are used as the probe signals. The two-dimensional image of the buried pipes is achieved by a correlation method and a back-projection algorithm. The experimental results show that both the plastic pipe and metallic pipe can be located with a range resolution of 10 cm. Furthermore, as the Golay complementary sequences are a pair of complementary sequences, the sum of their correlation function yields twice the value of the peak at the target position and zero elsewhere. Thus, compared with the stepped frequency signal radar or chaotic signal radar, the Golay-based radar can significantly improve the signal–noise ratio and has the capability of deep detection.

Author(s):  
Ryan Xiao ◽  
William Wang ◽  
Ang Li ◽  
Shengqiu Xu ◽  
Binghai Liu

Abstract With the development of semiconductor technology and the increment quantity of metal layers in past few years, backside EFA (Electrical Failure Analysis) technology has become the dominant method. In this paper, abnormally high Signal Noise Ratio (SNR) signal captured by Electro-Optical Probing (EOP)/Laser Voltage Probing (LVP) from backside is shown and the cause of these phenomena are studied. Based on the real case collection, two kinds of failure mode are summarized, and simulated experiments are performed. The results indicate that when a current path from power to ground is formed, the high SNR signal can be captured at the transistor which was on this current path. It is helpful of this consequence for FA to identify the failure mode by high SNR signal.


2014 ◽  
Vol 86 (24) ◽  
pp. 11972-11976 ◽  
Author(s):  
Ding Yuan ◽  
Lina Xiao ◽  
Jingchun Jia ◽  
Jie Zhang ◽  
Lianhuan Han ◽  
...  

2021 ◽  
Vol 13 (2) ◽  
pp. 241
Author(s):  
Yongkun Song ◽  
Tian Jin ◽  
Yongpeng Dai ◽  
Yongping Song ◽  
Xiaolong Zhou

Human pose reconstruction has been a fundamental research in computer vision. However, existing pose reconstruction methods suffer from the problem of wall occlusion that cannot be solved by a traditional optical sensor. This article studies a novel human target pose reconstruction framework using low-frequency ultra-wideband (UWB) multiple-input multiple-output (MIMO) radar and a convolutional neural network (CNN), which is used to detect targets behind the wall. In the proposed framework, first, we use UWB MIMO radar to capture the human body information. Then, target detection and tracking are used to lock the target position, and the back-projection algorithm is adopted to construct three-dimensional (3D) images. Finally, we take the processed 3D image as input to reconstruct the 3D pose of the human target via the designed 3D CNN model. Field detection experiments and comparison results show that the proposed framework can achieve pose reconstruction of human targets behind a wall, which indicates that our research can make up for the shortcomings of optical sensors and significantly expands the application of the UWB MIMO radar system.


Optik ◽  
2021 ◽  
pp. 166330
Author(s):  
Jiasai Ma ◽  
Jianxun Pan ◽  
Jing Wang ◽  
Wenguang Jiang ◽  
Zhenmei Yu
Keyword(s):  

1991 ◽  
Vol 9 (1) ◽  
pp. 120-121 ◽  
Author(s):  
David Allen ◽  
John Hillier

AbstractWe have secured spectra at high signal/noise ratio in a grid of points across the entire Homunculus Nebula surrounding the peculiar, massive star η Carinae. The data cover the wavelength range 420–1000 nm. Included are parts of the outer nebulosity dating from a prehistoric ejection episode. At a spatial resolution of about 1 arcsec we find dramatic differences in emission Ime ratios and profiles, sometimes in adjacent resolution elements.


Author(s):  
Han Wang ◽  
Songqing Zhang ◽  
Tingze Zhang ◽  
Junliang Liu ◽  
Zekai Zhang ◽  
...  
Keyword(s):  

1996 ◽  
Author(s):  
M. Offenberg ◽  
H. Münzel ◽  
D. Schubert ◽  
O. Schatz ◽  
F. Lärmer ◽  
...  

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