Zhonghai Wang

Intelligent Fusion Technology (United States)

Papers

Total Citations

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About

Zhonghai Wang is a researcher advancing the frontiers of space situational awareness (SSA) and autonomous systems through innovative sensor management and robotic emulation. His work addresses critical challenges in tracking and decision-making under constrained conditions, blending game theory, artificial intelligence, and robotics. Wang’s most cited paper, “Low frame rate video target localization and tracking testbed” (2013, 6 citations), introduces a saliency-based temporal association dependency (STAD) framework that robustly tracks targets despite significant appearance and location changes between frames—a key contribution for low-bandwidth or degraded sensing environments. He further developed an orbital emulator for pursuit-evasion game theoretic sensor management (2017, 4 citations), which uses omni-wheeled robots and robotic arms to simulate 3D satellite motion, enabling novel strategies for space object tracking and threat response. In “Autonomy in use for space situation awareness” (2019, 4 citations), Wang explores architectures like autonomy in motion (AIM) for dynamic data assessment, integrating AI and communications to enhance autonomous SSA systems. His work bridges theoretical frameworks with practical testbeds, offering tools and insights for students and researchers in aerospace, robotics, and intelligent systems.