Fei Zhan

Beijing Forestry University

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Jianren Wang

Yanshan University

Jieshan Qiu

Beijing University of Chemical Technology

Qidi Ren

Zhejiang University of Technology

Gang Wang

Dalian University of Technology

Qiang Dong

Hefei University

Tingting Wu

University of Jinan

Xiaochuan Ma

Institute of Acoustics

Liang Xu

University of Chinese Academy of Sciences

Yulan Meng

Dalian University

Hao Zhang

Yanshan University

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Chinese Academy of Sciences

Dalian University of Technology

Dalian University

University of Chinese Academy of Sciences

Beijing Institute of Nanoenergy and Nanosystems

Institute of Acoustics

Beijing University of Chemical Technology

Yanshan University

University of Science and Technology of China

Changchun Institute of Applied Chemistry

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K-distribution reverberation and reliable statistical approach study of sonar data

OCEANS 2016 - Shanghai (2016)

Chi Zhang Xiaochuan Ma Shuhao Zhang Fei Zhan

Performing reliable target detection in reverberation background is a critical problem demanding prompt solutions. Researching on the statistical characterization of reverberation envelope is significantly important for not only the CFAR detection, but also the environment detection and seafloor classification. Identified as a robust statistical model for shallow water reverberation envelope, K-distribution, which is introduced from radar clutter processing to sonar engineering, provides a physical interpretation of its parameters which are relevant to the environment parameters. Because different sonar data processing methods may lead to different results, we have to research on the reliable statistical approaches of processing sonar data, in order to obtain objective and credible conclusions. In this paper, we generate pseudo-random variables of K-distribution and introduce a series of statistical procedures to handle the random data. Then the distribution fitting, the parameter estimation of the distribution and the evaluation of fitting goodness could be made on the basis of these steps. Supported by an underwater experiment, we sampled a set of real data by a planar array. We illustrate the approach using the real data, and verify that the reverberation envelope of shallow water fits the K-distribution model well.

Envelope (radar)

Data set

Sonar signal processing

10.1109/oceansap.2016.7485424

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Citations (1)

Functional PAN-based monoliths with hierarchical structure for heavy metal removal

Chemical Engineering Journal (2016)

Gang Wang Jianren Wang Hao Zhang Fei Zhan Tingting Wu

Monolith

Polyacrylonitrile

Diethylenetriamine

10.1016/j.cej.2016.11.032

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Citations (25)

Electron transfer induced contact-electrification at oil and oleophobic dielectric interface

Nano Energy (2023)

Huaifang Qin Liang Xu Fei Zhan Zhong Lin Wang

Contact electrification

Thermionic emission

10.1016/j.nanoen.2023.108762

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Citations (14)

Surface-treated carbon electrodes with modified potential of zero charge for capacitive deionization

Water Research (2016)

Tingting Wu Gang Wang Fei Zhan Qiang Dong Qidi Ren

Capacitive Deionization

Carbon fibers

Nitric acid

10.1016/j.watres.2016.02.004

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Citations (204)

Salinity‐Difference‐Driven Power Generation by a Hybrid Capacitive Approach

Energy Technology (2017)

Fei Zhan Gang Wang Tingting Wu Qiang Dong Yulan Meng

Abstract The extraction of salinity gradient energy remains a challenging task. In this paper, we propose a new method for the extraction of salinity gradient energy by using a hybrid capacitor, which consists of a battery electrode and a porous carbon electrode. The potentials of the Na 4 Mn 9 O 18 (NMO) and activated carbon (AC) electrodes show opposite dependencies on salt concentration, so that as fresh water and salt water flow alternately through the hybrid capacitor, the voltage difference between the electrodes can be increased by 110 mV. Our results demonstrate the viability of this new method to harvest salinity gradient energy without using membranes or precious metals.

Carbon fibers

Potential difference

Osmotic power

10.1002/ente.201700436

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Citations (5)