Xiaohong Shen
Papers
1
Total Citations
26
H-Index
1
About
Xiaohong Shen is a leading researcher in sensor networks and signal processing, with a focus on source localization under challenging real-world constraints. Her work addresses a critical problem: accurately determining the position of a signal source when measurements are imperfect. In her highly cited 2020 paper, "Semidefinite Relaxation for Source Localization With Quantized ToA Measurements and Transmission Uncertainty in Sensor Networks," she introduced a novel semidefinite relaxation technique that overcomes the limitations of quantized Time-of-Arrival (ToA) data and unknown transmission parameters. This contribution is vital for applications ranging from radar and sonar to autonomous robots and intelligent transportation systems, where precise location information is essential. With over 26 citations, her research has provided a robust mathematical framework that improves localization accuracy even when sensor data is coarse or uncertain. Shen’s work bridges theoretical optimization and practical engineering, offering solutions that are both computationally efficient and resilient to real-world imperfections. Her achievements underscore her role in advancing sensor network reliability, making her a key figure in the field of distributed signal processing and localization.
Research Focus
Key Achievements
Top Papers
- 1