D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 32 Citations 5,832 310 World Ranking 5063 National Ranking 574

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Algorithm

Guisheng Liao focuses on Algorithm, Artificial intelligence, Radar imaging, Computer vision and Synthetic aperture radar. His primary area of study in Algorithm is in the field of Estimation theory. As a part of the same scientific family, Guisheng Liao mostly works in the field of Artificial intelligence, focusing on Pattern recognition and, on occasion, Learning rule, FSA-Red Algorithm and Algorithm design.

The various areas that Guisheng Liao examines in his Radar imaging study include Clutter and Remote sensing. His Computer vision research is multidisciplinary, incorporating elements of Inverse synthetic aperture radar and Fourier transform. His studies deal with areas such as Image registration, Focus, Subpixel rendering and Phase congruency as well as Synthetic aperture radar.

His most cited work include:

  • Multitarget identification and localization using bistatic MIMO radar systems (215 citations)
  • Fast communication: Joint DOD and DOA estimation for bistatic MIMO radar (180 citations)
  • Joint Range and Angle Estimation Using MIMO Radar With Frequency Diverse Array (160 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Algorithm, Synthetic aperture radar, Radar, Artificial intelligence and Clutter. The Algorithm study combines topics in areas such as Statistics and Signal, Direction of arrival. The concepts of his Synthetic aperture radar study are interwoven with issues in Inverse synthetic aperture radar, Radar imaging, Azimuth and Acoustics.

His studies in Radar integrate themes in fields like MIMO, Mimo radar, Waveform and Electronic engineering. His study explores the link between Artificial intelligence and topics such as Computer vision that cross with problems in Robustness. His research investigates the connection between Clutter and topics such as Radar horizon that intersect with problems in Envelope.

He most often published in these fields:

  • Algorithm (44.42%)
  • Synthetic aperture radar (29.78%)
  • Radar (26.30%)

What were the highlights of his more recent work (between 2019-2021)?

  • Algorithm (44.42%)
  • Radar (26.30%)
  • Synthetic aperture radar (29.78%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Algorithm, Radar, Synthetic aperture radar, MIMO and Clutter. His Covariance matrix and Estimation theory study, which is part of a larger body of work in Algorithm, is frequently linked to Object detection, bridging the gap between disciplines. His Radar study combines topics from a wide range of disciplines, such as Mimo radar and Electronic engineering.

His Synthetic aperture radar research also covers Artificial intelligence and Computer vision studies. Within one scientific family, he focuses on topics pertaining to Inverse synthetic aperture radar under Computer vision, and may sometimes address concerns connected to Bistatic radar, Scaling, Point and Angular velocity. Guisheng Liao has researched Clutter in several fields, including Constant false alarm rate, Moving target indication, Amplitude distribution, Electromagnetic spectrum and Early-warning radar.

Between 2019 and 2021, his most popular works were:

  • Model-Aided Deep Neural Network for Source Number Detection (8 citations)
  • Super-Resolution Range and Velocity Estimations With OFDM Integrated Radar and Communications Waveform (4 citations)
  • Robust Null Broadening Beamforming Based on Covariance Matrix Reconstruction via Virtual Interference Sources (4 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Algorithm

Guisheng Liao mostly deals with Algorithm, Radar, Interference, Covariance matrix and Beamforming. His study in Algorithm is interdisciplinary in nature, drawing from both MIMO, Pulse repetition frequency and Aliasing. His Radar research incorporates themes from Smoothing, Waveform, Base station, Communications system and Electronic engineering.

His Beamforming research focuses on subjects like Spatial frequency, which are linked to Quantization, Control theory, Mimo radar and Null. His study focuses on the intersection of Estimation theory and fields such as Rotation with connections in the field of Synthetic aperture radar. His Fourier transform research integrates issues from Clutter and Constant false alarm rate.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Multitarget identification and localization using bistatic MIMO radar systems

Haidong Yan;Jun Li;Guisheng Liao.
EURASIP Journal on Advances in Signal Processing (2008)

382 Citations

Fast communication: Joint DOD and DOA estimation for bistatic MIMO radar

Ming Jin;Guisheng Liao;Jun Li.
Signal Processing (2009)

276 Citations

Fast communication: a fast algorithm for 2-D direction-of-arrival estimation

Yuntao Wu;Guisheng Liao;H. C. So.
Signal Processing (2003)

222 Citations

Ground Moving Targets Imaging Algorithm for Synthetic Aperture Radar

Shengqi Zhu;Guisheng Liao;Yi Qu;Zhengguang Zhou.
IEEE Transactions on Geoscience and Remote Sensing (2011)

216 Citations

Joint Range and Angle Estimation Using MIMO Radar With Frequency Diverse Array

Jingwei Xu;Guisheng Liao;Shengqi Zhu;Lei Huang.
IEEE Transactions on Signal Processing (2015)

212 Citations

An Eigenstructure Method for Estimating DOA and Sensor Gain-Phase Errors

Aifei Liu;Guisheng Liao;Cao Zeng;Zhiwei Yang.
IEEE Transactions on Signal Processing (2011)

204 Citations

A New Method for Radar High-Speed Maneuvering Weak Target Detection and Imaging

Shengqi Zhu;Guisheng Liao;Dong Yang;Haihong Tao.
IEEE Geoscience and Remote Sensing Letters (2014)

128 Citations

Deceptive jamming suppression with frequency diverse MIMO radar

Jingwei Xu;Guisheng Liao;Shengqi Zhu;Hing Cheung So.
Signal Processing (2015)

121 Citations

Adaptive OFDM Integrated Radar and Communications Waveform Design Based on Information Theory

Yongjun Liu;Guisheng Liao;Jingwei Xu;Zhiwei Yang.
IEEE Communications Letters (2017)

113 Citations

Long-Time Coherent Integration for Weak Maneuvering Target Detection and High-Order Motion Parameter Estimation Based on Keystone Transform

Penghui Huang;Guisheng Liao;Zhiwei Yang;Xiang-Gen Xia.
IEEE Transactions on Signal Processing (2016)

109 Citations

Best Scientists Citing Guisheng Liao

Wen-Qin Wang

Wen-Qin Wang

University of Electronic Science and Technology of China

Publications: 78

Mengdao Xing

Mengdao Xing

Xidian University

Publications: 48

Zheng Bao

Zheng Bao

Xidian University

Publications: 31

Hing Cheung So

Hing Cheung So

City University of Hong Kong

Publications: 29

Xiang-Gen Xia

Xiang-Gen Xia

University of Delaware

Publications: 28

Wei Liu

Wei Liu

Shanghai Jiao Tong University

Publications: 23

Yimin Zhang

Yimin Zhang

Temple University

Publications: 19

Yonina C. Eldar

Yonina C. Eldar

Weizmann Institute of Science

Publications: 16

Hongwei Liu

Hongwei Liu

Xidian University

Publications: 14

Zhi Sun

Zhi Sun

Tsinghua University

Publications: 14

Moeness G. Amin

Moeness G. Amin

Villanova University

Publications: 12

Zhang Yi

Zhang Yi

Sichuan University

Publications: 10

Qing Huo Liu

Qing Huo Liu

Duke University

Publications: 9

Tat Soon Yeo

Tat Soon Yeo

National University of Singapore

Publications: 9

Braham Himed

Braham Himed

United States Air Force Research Laboratory

Publications: 9

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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