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.
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