Phanassanun Thajai
Papers
1
Total Citations
2
H-Index
1
About
Phanassanun Thajai is an emerging researcher in sensor fusion and estimation theory, with a focus on improving the accuracy of angle estimation for robotics, navigation, and biomedical applications. Their most-cited work, "Comparative Analysis of Sensor Fusion for Angle Estimation Using Kalman and Complementary Filters" (2024), systematically evaluates two critical filtering techniques—the Kalman filter and the complementary filter—using data from the IMU6050 sensor, which integrates accelerometer and gyroscope readings. By comparing these methods, Thajai provides valuable insights into their respective strengths and trade-offs, offering practical guidance for engineers seeking to optimize performance in real-time motion tracking systems. Although early in their career, with 2 citations to date, this contribution addresses a foundational challenge in sensor fusion, demonstrating a clear understanding of how to balance computational efficiency with estimation accuracy. Thajai’s work is particularly relevant for developers of autonomous systems, wearable health monitors, and robotic platforms where precise orientation data is essential. As the field of sensor fusion continues to expand, Thajai’s comparative analysis serves as a useful reference for both students and practitioners aiming to select appropriate filtering strategies for their specific applications.
Research Focus
Key Achievements
Top Papers
- 1