Xusheng Yang
Papers
3
Total Citations
157
H-Index
3
About
Xusheng Yang is a researcher whose work sits at the intersection of wireless sensor networks, distributed estimation, and autonomous systems. Best known for advancing the field of multi-sensor fusion, Yang has made significant contributions to how unmanned and networked systems track and localize targets in complex, real-world environments. His 2015 paper, "Multi-Rate Distributed Fusion Estimation for Sensor Network-Based Target Tracking," garnered 68 citations and introduced a hierarchical two-stage fusion framework that elegantly balances energy efficiency with tracking accuracy — a critical trade-off in resource-constrained wireless sensor networks. Building on this foundation, his 2016 work on hybrid sequential fusion estimation (56 citations) tackled the challenging problem of asynchronous sensor networks, compensating for timing mismatches through an innovative time-varying fading factor. That same year, Yang extended his fusion methodology to mobile robot localization using received signal strength measurements, demonstrating the broad applicability of his approaches across robotics and networked sensing. Collectively, his research has garnered over 150 citations, establishing him as a meaningful contributor to the design of robust, efficient estimation algorithms for next-generation intelligent sensing systems.
Research Focus
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Top Papers
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