What is she best known for?
The fields of study she is best known for:
- Statistics
- Radar
- Artificial intelligence
Her main research concerns Radar, Clutter, Algorithm, Constant false alarm rate and Detector.
The concepts of her Radar study are interwoven with issues in Range and Electronic engineering.
Her Clutter research is multidisciplinary, incorporating elements of Remote sensing, Matched filter, Gaussian noise, Artificial intelligence and Pattern recognition.
Her work deals with themes such as Speech recognition, Continuous-wave radar, Estimator, Statistics and Signal processing, which intersect with Algorithm.
The Constant false alarm rate study combines topics in areas such as Covariance matrix and Stationary target indication.
As part of one scientific family, Maria Greco deals mainly with the area of Detector, narrowing it down to issues related to the Likelihood-ratio test, and often Performance prediction.
Her most cited work include:
- Covariance matrix estimation for CFAR Detection in correlated heavy tailed clutter (293 citations)
- High resolution sea clutter data: statistical analysis of recorded live data (227 citations)
- Statistical analyses of measured radar ground clutter data (174 citations)
What are the main themes of her work throughout her whole career to date?
Radar, Clutter, Algorithm, Remote sensing and Electronic engineering are her primary areas of study.
Radar tracker is the focus of her Radar research.
Maria Greco interconnects Detector, Constant false alarm rate, Matched filter, Gaussian noise and Pattern recognition in the investigation of issues within Clutter.
Maria Greco works mostly in the field of Algorithm, limiting it down to topics relating to Estimator and, in certain cases, Upper and lower bounds, Estimation theory, Mean squared error, Applied mathematics and Covariance matrix, as a part of the same area of interest.
She focuses mostly in the field of Remote sensing, narrowing it down to topics relating to Bistatic radar and, in certain cases, Continuous-wave radar and Ambiguity function.
The study incorporates disciplines such as Direction of arrival, Monopulse radar and Compressed sensing in addition to Electronic engineering.
She most often published in these fields:
- Radar (38.99%)
- Clutter (28.52%)
- Algorithm (27.44%)
What were the highlights of her more recent work (between 2015-2021)?
- Radar (38.99%)
- Algorithm (27.44%)
- Signal processing (7.58%)
In recent papers she was focusing on the following fields of study:
Her scientific interests lie mostly in Radar, Algorithm, Signal processing, Applied mathematics and Interference.
Her Radar research focuses on Passive radar in particular.
The various areas that Maria Greco examines in her Algorithm study include False alarm, Statistical hypothesis testing and MIMO.
Her Signal processing research incorporates themes from Constant false alarm rate, Artificial intelligence and Multistatic radar.
Within one scientific family, Maria Greco focuses on topics pertaining to Pattern recognition under Artificial intelligence, and may sometimes address concerns connected to Clutter.
Her Applied mathematics research is multidisciplinary, incorporating perspectives in Semiparametric model, Estimator, Scatter matrix, Estimation theory and Upper and lower bounds.
Between 2015 and 2021, her most popular works were:
- Spectrum sensing and sharing for cognitive radars (48 citations)
- Cognitive Radars: On the Road to Reality: Progress Thus Far and Possibilities for the Future (44 citations)
- Performance Bounds for Parameter Estimation under Misspecified Models: Fundamental Findings and Applications (39 citations)
In her most recent research, the most cited papers focused on:
- Statistics
- Radar
- Artificial intelligence
Maria Greco mainly focuses on Radar, Signal processing, Applied mathematics, Algorithm and Cramér–Rao bound.
Her Radar engineering details study in the realm of Radar interacts with subjects such as Set.
Her biological study deals with issues like Constant false alarm rate, which deal with fields such as Pattern recognition, Speech recognition, Detector and Additive white Gaussian noise.
Her Algorithm research incorporates themes from Signal and Geolocation.
She has researched Cramér–Rao bound in several fields, including Covariance matrix and Probability density function.
Her Focus study integrates concerns from other disciplines, such as Clutter and Bistatic radar.
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