Abdurazag Ghila
Papers
1
Total Citations
2
H-Index
1
About
Abdurazag Ghila’s research centers on low-cost inertial navigation systems and sensor fusion for autonomous vehicle guidance. His most influential work introduces a cascade Kalman filter configuration for integrating an inertial measurement unit (IMU) with GPS, specifically designed for land vehicle navigation and car-like robots. By employing an extended Kalman filter in a loosely coupled, cascade mode, Ghila developed a computationally efficient algorithm that enhances positioning accuracy without requiring expensive hardware. His approach, validated through MATLAB simulations, offers a practical solution for real-time navigation in GPS-denied or degraded environments. While his highly cited paper has garnered 2 citations, its conceptual contribution lies in demonstrating how cascaded filtering can mitigate drift in low-cost IMUs—a critical challenge for autonomous robotics and automotive applications. Ghila’s work bridges the gap between theoretical estimation theory and affordable, deployable navigation systems, making it a valuable reference for researchers working on sensor fusion, mobile robotics, and intelligent transportation.
Research Focus
Key Achievements
Top Papers
- 1