Environmental signal processing: Three‐dimensional matched‐field processing with a vertical array

1990 ◽  
Vol 87 (4) ◽  
pp. 1553-1556 ◽  
Author(s):  
John S. Perkins ◽  
W. A. Kuperman
Keyword(s):  
Signal Processing ◽  
Three Dimensional ◽  
Vertical Array ◽  
Matched Field Processing ◽  
Environmental Signal

scholarly journals Prospects of the WSR-88D Radar for Cloud Studies

2011 ◽  
Vol 50 (4) ◽  
pp. 859-872 ◽  
Author(s):  
Valery M. Melnikov ◽  
Dusan S. Zrnić ◽  
Richard J. Doviak ◽  
Phillip B. Chilson ◽  
David B. Mechem ◽  
...  
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Three Dimensional ◽  
High Sensitivity ◽  
Doppler Velocity ◽  
Cloud Data ◽  
Three Dimensional Mapping ◽  
Spectrum Width ◽  
Differential Reflectivity ◽  
Dimensional Mapping

AbstractSounding of nonprecipitating clouds with the 10-cm wavelength Weather Surveillance Radar-1988 Doppler (WSR-88D) is discussed. Readily available enhancements to signal processing and volume coverage patterns of the WSR-88D allow observations of a variety of clouds with reflectivities as low as −25 dBZ (at a range of 10 km). The high sensitivity of the WSR-88D, its wide velocity and unambiguous range intervals, and the absence of attenuation allow accurate measurements of the reflectivity factor, Doppler velocity, and spectrum width fields in clouds to ranges of about 50 km. Fields of polarimetric variables in clouds, observed with a research polarimetric WSR-88D, demonstrate an abundance of information and help to resolve Bragg and particulate scatter. The scanning, Doppler, and polarimetric capabilities of the WSR-88D allow real-time, three-dimensional mapping of cloud processes, such as transformations of hydrometeors between liquid and ice phases. The presence of ice particles is revealed by high differential reflectivities and the lack of correlation between reflectivity and differential reflectivity in clouds in contrast to that found for rain. Pockets of high differential reflectivities are frequently observed in clouds; maximal values of differential reflectivity exceed 8 dB, far above the level observed in rain. The establishment of the WSR-88D network consisting of 157 polarimetric radars can be used to collect cloud data at any radar site, making the network a potentially powerful tool for climatic studies.

Fabrication and electrochemical characterization of super-capacitor based on three-dimensional composite structure of graphene and a vertical array of carbon nanotubes

2018 ◽  
Vol 52 (22) ◽  
pp. 3039-3044 ◽  
Author(s):  
Daniel Choi ◽  
Eui-Hyeok Yang ◽  
Waqas Gill ◽  
Aaron Berndt ◽  
Jung-Rae Park ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Vapor Deposition ◽  
Composite Structure ◽  
Graphene Layer ◽  
Three Dimensional ◽  
Chemical Vapor ◽  
Deposition Process ◽  
Silicon Substrates ◽  
Vertical Array ◽  
Pressure Chemical

We have demonstrated a three-dimensional composite structure of graphene and carbon nanotubes as electrodes for super-capacitors. The goal of this study is to fabricate and test the vertically grown carbon nanotubes on the graphene layer acting as a spacer to avoid self-aggregation of the graphene layers while realizing high active surface area for high energy density, specific capacitance, and power density. A vertical array of carbon nanotubes on silicon substrates was grown by a low-pressure chemical vapor deposition process using anodized aluminum oxide nanoporous template fabricated on silicon substrates. Subsequently, a graphene layer was grown by another low-pressure chemical vapor deposition process on top of a vertical array of carbon nanotubes. The Raman spectra confirmed the successful growth of carbon nanotubes followed by the growth of high-quality graphene. The average measured capacitance of the three-dimensional composite structure of graphene-carbon nanotube was 780 µFcm−2 at 100 mVs−1.

Three‐dimensional integration of resonant tunneling structures for signal processing and three‐state logic

1988 ◽  
Vol 52 (25) ◽  
pp. 2163-2164 ◽  
Author(s):  
Robert C. Potter ◽  
Amir A. Lakhani ◽  
Dana Beyea ◽  
Harry Hier ◽  
Erica Hempfling ◽  
...  
Keyword(s):  
Signal Processing ◽  
Resonant Tunneling ◽  
Three Dimensional

scholarly journals Millimeter-Wave Array Radar-Based Human Gait Recognition Using Multi-Channel Three-Dimensional Convolutional Neural Network

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5466 ◽  
Author(s):  
Xinrui Jiang ◽  
Ye Zhang ◽  
Qi Yang ◽  
Bin Deng ◽  
Hongqiang Wang
Keyword(s):  
Neural Network ◽  
Signal Processing ◽  
Millimeter Wave ◽  
Gait Recognition ◽  
Three Dimensional ◽  
Human Gait ◽  
Radar Signal ◽  
Learning Technology ◽  
Motion Speed ◽  
Signal Processing Algorithms

At present, there are two obvious problems in radar-based gait recognition. First, the traditional radar frequency band is difficult to meet the requirements of fine identification with due to its low carrier frequency and limited micro-Doppler resolution. Another significant problem is that radar signal processing is relatively complex, and the existing signal processing algorithms are poor in real-time usability, robustness and universality. This paper focuses on the two basic problems of human gait detection with radar and proposes a human gait classification and recognition method based on millimeter-wave array radar. Based on deep-learning technology, a multi-channel three-dimensional convolution neural network is proposed on the basis of improving the residual network, which completes the classification and recognition of human gait through the hierarchical extraction and fusion of multi-dimensional features. Taking the three-dimensional coordinates, motion speed and intensity of strong scattering points in the process of target motion as network inputs, multi-channel convolution is used to extract motion features, and the classification and recognition of typical daily actions are completed. The experimental results show that we have more than 92.5% recognition accuracy for common gait categories such as jogging and normal walking.

Inversion of Pressure Data on a Vertical Array for Sea Floor Geoacoustic Properties

1998 ◽  
Vol 06 (01n02) ◽  
pp. 269-289 ◽  
Author(s):  
Purnima Ratilal ◽  
Peter Gerstoft ◽  
Joo Thiam Goh ◽  
Keng Pong Yeo
Keyword(s):  
Ambient Noise ◽  
Historical Data ◽  
Low Frequency ◽  
Real Data ◽  
Vertical Array ◽  
Trial Site ◽  
Matched Field Processing ◽  
High Frequencies ◽  
Sea Floor ◽  
Line Array

Estimation of the integral geoacoustic properties of the sea floor based on real data drawn from a shallow water site is presented. Two independent inversion schemes are used to deduce these properties. The first is matched-field processing of the pressure field on a vertical line array due to a projected source. The second approach is the inversion of ambient noise on a vertical array. Matched-field processing has shown to be successful in the inversion of high quality field data. Here, we show that it is also feasible with a more practical and less expensive data collection scheme. It will also be shown that low frequency inversion is more robust to variation and fluctuation in the propagating medium, whereas high frequencies are more sensitive to mismatches in a varying medium. A comparison is made of the estimates obtained from the two techniques and also with available historical data of the trial site.

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