Arash Maskooki

Papers

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About

Arash Maskooki is a researcher whose work lies at the intersection of ultra-wideband (UWB) technology and precise indoor localization—a critical challenge for robotics, IoT, and smart environments. His most cited paper, "An Accurate 3D UWB Hyperbolic Localization in Indoor Multipath Environment Using Iterative Taylor-Series Estimation" (2013, 15 citations), introduces a robust method for three-dimensional positioning by solving time difference of arrival (TDOA) equations in challenging multipath conditions. By employing an iterative Taylor-series estimation, Maskooki’s approach significantly improves accuracy over conventional methods, enabling reliable source localization from hyperboloid intersections. This contribution addresses a fundamental bottleneck in indoor navigation, where GPS fails and signal reflections distort measurements. Though his citation count reflects a focused, emerging impact, the work is notable for its practical relevance to UWB systems—a technology increasingly adopted in precision tracking and autonomous systems. Maskooki’s research demonstrates a keen ability to translate complex signal processing theory into actionable solutions for real-world environments, marking him as a contributor to the evolution of resilient, high-accuracy localization in non-ideal conditions.