Abdelrahman El-Naggar

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About

Abdelrahman El-Naggar is a researcher specializing in indoor localization, sensor fusion, and navigation systems. His work addresses the critical challenge of accurate positioning in GPS-denied environments, with applications in autonomous robotics, asset tracking, and smart building technologies. His most cited paper, "Indoor Positioning Using WiFi RSSI Trilateration and INS Sensor Fusion System Simulation" (2019, 14 citations), proposes a novel method that fuses WiFi RSSI trilateration with inertial navigation system (INS) data. This hybrid approach overcomes the limitations of WiFi-only positioning—such as signal instability and low accuracy—by integrating INS for continuous, drift-corrected localization. El-Naggar’s contributions are significant for advancing reliable indoor navigation, particularly in complex environments where traditional GPS fails. His work has been cited in subsequent research on sensor fusion and IoT-based positioning systems, reflecting its practical impact. By combining simulation with real-world applicability, El-Naggar has laid groundwork for more robust, cost-effective indoor localization solutions, making him a notable figure in the field of wireless and inertial navigation systems.