What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Radar
- Quantum mechanics
Ram M. Narayanan mainly focuses on Radar, Radar imaging, Artificial intelligence, Pulse-Doppler radar and Continuous-wave radar.
The study incorporates disciplines such as Waveform, Electronic engineering and Remote sensing in addition to Radar.
His research integrates issues of Feature extraction and Electromagnetic interference in his study of Remote sensing.
His Radar imaging research is multidisciplinary, incorporating elements of Synthetic aperture radar, Image processing, Noise and Ultra-wideband.
His Artificial intelligence research incorporates elements of Computer vision and Pattern recognition.
His research in Pulse-Doppler radar intersects with topics in Acoustics, Algorithm and Bistatic radar.
His most cited work include:
- On the Opportunities and Challenges in Microwave Medical Sensing and Imaging (146 citations)
- Noise estimation in remote sensing imagery using data masking (126 citations)
- Three-dimensional interferometric ISAR imaging for target scattering diagnosis and modeling (119 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Radar, Remote sensing, Radar imaging, Electronic engineering and Continuous-wave radar.
His Radar research incorporates themes from Acoustics and Waveform.
His work carried out in the field of Remote sensing brings together such families of science as Wavelength, Ground-penetrating radar and Polarimetry.
His biological study spans a wide range of topics, including Synthetic aperture radar, Computer vision, Artificial intelligence and Optics.
In his research, Interference is intimately related to Radio frequency, which falls under the overarching field of Electronic engineering.
He works mostly in the field of Continuous-wave radar, limiting it down to topics relating to Pulse-Doppler radar and, in certain cases, Pulse repetition frequency, as a part of the same area of interest.
He most often published in these fields:
- Radar (52.55%)
- Remote sensing (28.31%)
- Radar imaging (25.05%)
What were the highlights of his more recent work (between 2017-2021)?
- Radar (52.55%)
- Waveform (15.68%)
- Interference (5.09%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Radar, Waveform, Interference, Radio frequency and Electronic engineering.
His Radar study combines topics in areas such as Real-time computing and Bandwidth.
His Waveform study also includes
- Acoustics which intersects with area such as Signal, Nondestructive testing and Microwave imaging,
- Multistatic radar and Computer vision most often made with reference to Mutual information.
In his study, Pulse is strongly linked to Distortion, which falls under the umbrella field of Electronic engineering.
While the research belongs to areas of Clutter, he spends his time largely on the problem of Radar cross-section, intersecting his research to questions surrounding Calibration, Synthetic aperture radar and Remote sensing.
Ram M. Narayanan has included themes like Terrain and Filter in his Radar imaging study.
Between 2017 and 2021, his most popular works were:
- Avoidance of Time-Varying Radio Frequency Interference With Software-Defined Cognitive Radar (21 citations)
- Application of Unidirectional Carbon-Fiber-Reinforced-Polymer Laminas in Circuit-Analog Absorbers (11 citations)
- Mitigation of target distortion in pulse-agile sensors via Richardson─Lucy deconvolution (10 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Radar
- Artificial intelligence
Ram M. Narayanan spends much of his time researching Radar, Interference, Radio frequency, Electronic engineering and Waveform.
His Radar research is multidisciplinary, relying on both Reflection coefficient, Real-time computing and Cognitive radar.
His work deals with themes such as Interference, Algorithm, Electromagnetic interference and Bandwidth, which intersect with Interference.
His Electronic engineering study combines topics from a wide range of disciplines, such as Stochastic modelling, Chaotic, Distortion and Nonlinear system.
His Waveform research focuses on Acoustics and how it connects with Microwave imaging, Nondestructive testing and Signal.
His study in Doppler radar is interdisciplinary in nature, drawing from both Point spread function, Radar imaging, Feature extraction, Pattern recognition and Richardson–Lucy deconvolution.
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