Khaled Sharaf
Papers
1
Total Citations
14
H-Index
1
About
Khaled Sharaf is a researcher specializing in indoor positioning systems, sensor fusion, and navigation technologies. His work addresses the critical challenge of accurate localization in environments where GPS is unavailable, such as inside buildings, tunnels, or urban canyons. Sharaf’s most-cited paper, “Indoor Positioning Using WiFi RSSI Trilateration and INS Sensor Fusion System Simulation” (2019), proposes a hybrid method that combines WiFi signal strength trilateration with inertial navigation system (INS) data. This fusion approach overcomes the limitations of WiFi-only positioning—such as signal instability and multipath interference—by leveraging INS sensors (accelerometers, gyroscopes) for continuous, drift-corrected tracking. With 14 citations, the paper has influenced subsequent work in autonomous robotics, asset tracking, and navigation for the visually impaired. Sharaf’s contributions are particularly relevant for smart building applications, where reliable indoor positioning enables everything from emergency response to personalized retail experiences. His work exemplifies the practical engineering needed to bridge theoretical algorithms and real-world deployment, making him a notable figure in the growing field of ubiquitous location-based services.
Research Focus
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Top Papers
- 1