Study on the characteristics of underwater target laser echo based on pulse broadening

2021 ◽  
Author(s):  
Yujia Wang ◽  
Siguang Zong ◽  
Xin Zhang
Keyword(s):  
Underwater Target ◽  
Pulse Broadening

A morphological and energy-dispersive x-ray spectroscopy (EDS) investigation of separator-grade cellophane

1994 ◽  
Vol 52 ◽  
pp. 430-431
Author(s):  
Michael E. Rock ◽  
Vern Kennedy ◽  
Bhaskar Deodhar ◽  
Thomas G. Stoebe
Keyword(s):  
Extrusion Process ◽  
Morphological Characterization ◽  
Energy Dispersive ◽  
Regenerated Cellulose ◽  
Battery System ◽  
X Ray ◽  
Functional Differences ◽  
Transmission Electron ◽  
Separator Material ◽  
Underwater Target

Cellophane is a composite polymer material, made up of regenerated cellulose (usually derived from wood pulp) which has been chemically transformed into "viscose", then formed into a (1 mil thickness) transparent sheet through an extrusion process. Although primarily produced for the food industry, cellophane's use as a separator material in the silver-zinc secondary battery system has proved to be another important market. We examined 14 samples from five producers of cellophane, which are being evaluated as the separator material for a silver/zinc alkaline battery system in an autonomous underwater target vehicle. Our intent was to identify structural and/or chemical differences between samples which could be related to the functional differences seen in the lifetimes of these various battery separators. The unused cellophane samples were examined by transmission electron microscopy (TEM) and energy dispersive X-ray spectroscopy (EDS). Cellophane samples were cross sectioned (125-150 nm) using a diamond knife on a RMC MT-6000 ultramicrotome. Sections were examined in a Philips 430-T TEM at 200 kV. Analysis included morphological characterization, and EDS (for chemical composition). EDS was performed using an EDAX windowless detector.

scholarly journals Underwater Acoustic Target Recognition Based on Depthwise Separable Convolution Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1429
Author(s):  
Gang Hu ◽  
Kejun Wang ◽  
Liangliang Liu
Keyword(s):  
Feature Extraction ◽  
Target Recognition ◽  
Target Feature ◽  
Underwater Acoustic ◽  
Radiated Noise ◽  
Automatic Feature Extraction ◽  
Acoustic Target ◽  
And Cluster Analysis ◽  
Underwater Target ◽  
The One

Facing the complex marine environment, it is extremely challenging to conduct underwater acoustic target feature extraction and recognition using ship-radiated noise. In this paper, firstly, taking the one-dimensional time-domain raw signal of the ship as the input of the model, a new deep neural network model for underwater target recognition is proposed. Depthwise separable convolution and time-dilated convolution are used for passive underwater acoustic target recognition for the first time. The proposed model realizes automatic feature extraction from the raw data of ship radiated noise and temporal attention in the process of underwater target recognition. Secondly, the measured data are used to evaluate the model, and cluster analysis and visualization analysis are performed based on the features extracted from the model. The results show that the features extracted from the model have good characteristics of intra-class aggregation and inter-class separation. Furthermore, the cross-folding model is used to verify that there is no overfitting in the model, which improves the generalization ability of the model. Finally, the model is compared with traditional underwater acoustic target recognition, and its accuracy is significantly improved by 6.8%.

scholarly journals Bio-Inspired Covert Active Sonar Strategy

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2436 ◽  
Author(s):  
Jiajia Jiang ◽  
Xianquan Wang ◽  
Fajie Duan ◽  
Chunyue Li ◽  
Xiao Fu ◽  
...  
Keyword(s):  
Marine Mammals ◽  
Estimation Method ◽  
Sperm Whale ◽  
Waveform Design ◽  
Velocity Estimation ◽  
Estimation Methods ◽  
Range Resolution ◽  
Active Sonar ◽  
Ocean Noise ◽  
Underwater Target

The covertness of the active sonar is a very important issue and the sonar signal waveform design problem was studied to improve covertness of the system. Many marine mammals produce call pulses for communication and echolocation, and existing interception systems normally classify these biological signals as ocean noise and filter them out. Based on this, a bio-inspired covert active sonar strategy was proposed. The true, rather than man-made sperm whale, call pulses were used to serve as sonar waveforms so as to ensure the camouflage ability of sonar waveforms. A range and velocity measurement combination (RVMC) was designed by using two true sperm whale call pulses which had excellent range resolution (RR) and large Doppler tolerance (DT). The range and velocity estimation methods were developed based on the RVMC. In the sonar receiver, the correlation technology was used to confirm the start and end time of sonar signals and their echoes, and then based on the developed range and velocity estimation method, the range and velocity of the underwater target were obtained. Then, the RVMC was embedded into the true sperm whale call-train to improve the camouflage ability of the sonar signal-train. Finally, experiment results were provided to verify the performance of the proposed method.

Measurement of underwater target radiated noise based on nested biconical array

2021 ◽  
Vol 174 ◽  
pp. 107801
Author(s):  
Jie Shi ◽  
Zhichao Li ◽  
Heying Li ◽  
Yuhan Zhang
Keyword(s):  
Radiated Noise ◽  
Underwater Target

Higher-order polarization mode dispersion: new expressions, induced pulse broadening, and its compensation

2003 ◽  
Vol 228 (4-6) ◽  
pp. 331-339
Author(s):  
G.X. Ning ◽  
S. Aditya ◽  
P. Shum ◽  
C.Q. Wu ◽  
Y.D. Gong ◽  
...  
Keyword(s):  
Polarization Mode Dispersion ◽  
Higher Order ◽  
Polarization Mode ◽  
Mode Dispersion ◽  
Pulse Broadening
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