Shayan Shokri

Iran University of Science and Technology

Papers

Total Citations

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About

Shayan Shokri is a researcher whose work sits at the intersection of navigation, signal processing, and control systems, with a particular focus on enhancing the precision of Global Positioning System (GPS) technology. His most notable contribution is the development of a novel **Fuzzy Weighted Kalman Filter**, designed to improve GPS positioning accuracy. While the standard Kalman Filter is a cornerstone of navigation and robotic motion planning, Shokri’s innovation introduces a fuzzy logic-based weighting mechanism that adapts to dynamic conditions, offering a more robust and precise solution for real-world applications. Though his most-cited work currently holds 3 citations, it represents a promising step forward in a field where incremental improvements can have significant practical impact. Shokri’s research is especially relevant for engineers and scientists working on autonomous systems, drone navigation, and mobile robotics, where reliable positioning is critical. His work demonstrates a thoughtful integration of fuzzy logic with classical estimation theory, pointing toward a future where adaptive algorithms become standard in high-precision navigation.