What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Electrical engineering
- Statistics
His main research concerns Inertial navigation system, Global Positioning System, Kalman filter, GPS/INS and Inertial measurement unit.
His Inertial navigation system research includes themes of Control theory, Control engineering, Autoregressive model, GPS signals and Algorithm.
The various areas that Aboelmagd Noureldin examines in his Global Positioning System study include Artificial neural network, Navigation system, Artificial intelligence and Computer vision.
His research integrates issues of Gyroscope, Dead reckoning and Simulation in his study of Kalman filter.
His GPS/INS study combines topics in areas such as Real-time computing, Adaptive neuro fuzzy inference system and Sensor fusion.
His Inertial measurement unit research includes elements of Extended Kalman filter, Calibration, Speech recognition, Noise and Electronic engineering.
His most cited work include:
- Performance Enhancement of MEMS-Based INS/GPS Integration for Low-Cost Navigation Applications (245 citations)
- Wavelet Transform for Structural Health Monitoring: A Compendium of Uses and Features: (224 citations)
- Fundamentals of Inertial Navigation, Satellite-based Positioning and their Integration (202 citations)
What are the main themes of his work throughout his whole career to date?
Aboelmagd Noureldin mostly deals with Global Positioning System, Real-time computing, Inertial navigation system, Inertial measurement unit and Kalman filter.
His Global Positioning System research incorporates themes from Simulation and Navigation system.
His Real-time computing research integrates issues from Wireless, GNSS applications, Multipath propagation, Electronic engineering and Robustness.
His work carried out in the field of Inertial navigation system brings together such families of science as Control theory, Artificial neural network, Control engineering, Satellite navigation and Sensor fusion.
Aboelmagd Noureldin has included themes like Gyroscope, Odometer and Extended Kalman filter in his Inertial measurement unit study.
The Kalman filter study combines topics in areas such as Observability, Adaptive neuro fuzzy inference system and Noise.
He most often published in these fields:
- Global Positioning System (47.06%)
- Real-time computing (36.68%)
- Inertial navigation system (35.29%)
What were the highlights of his more recent work (between 2017-2021)?
- Real-time computing (36.68%)
- GNSS applications (15.57%)
- Global Positioning System (47.06%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Real-time computing, GNSS applications, Global Positioning System, Inertial measurement unit and Inertial navigation system.
The concepts of his Real-time computing study are interwoven with issues in Radar, Odometer and Network packet.
His GNSS applications study integrates concerns from other disciplines, such as Positioning system, Multipath propagation and Navigation system.
His biological study spans a wide range of topics, including Signal, Road surface and Robustness.
His Inertial measurement unit study combines topics from a wide range of disciplines, such as Azimuth, Gyroscope, Pseudorange, Kalman filter and Wavelet transform.
His work is dedicated to discovering how Inertial navigation system, Extended Kalman filter are connected with Control engineering, Linearization and Nonlinear system and other disciplines.
Between 2017 and 2021, his most popular works were:
- Towards a Practical Crowdsensing System for Road Surface Conditions Monitoring (32 citations)
- GNSS Error Sources (12 citations)
- Novel EKF-Based Vision/Inertial System Integration for Improved Navigation (10 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Electrical engineering
- Statistics
His primary scientific interests are in GNSS applications, Real-time computing, Inertial navigation system, Inertial measurement unit and Global Positioning System.
His research in GNSS applications intersects with topics in Heading and Remote sensing.
He focuses mostly in the field of Real-time computing, narrowing it down to topics relating to Network packet and, in certain cases, Traffic congestion, Information system and Intelligent sensor.
Inertial navigation system is closely attributed to Satellite system in his study.
His study in Inertial measurement unit is interdisciplinary in nature, drawing from both Kalman filter, Intelligent transportation system and Multipath propagation.
His studies in Global Positioning System integrate themes in fields like Navigation system, Extended Kalman filter and Road surface.
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.
