RSS-Based Localization Techniques With Large-Scale Experimental Evaluation

作者：Yingquan Li, Bodhibrata Mukhopadhyay, M. Alouini · 发表于：IEEE Transactions on Vehicular Technology · 年份：2026 · DOI：10.1109/tvt.2025.3593304 · 被引用次数：6 · 研究领域：Computer Science

Signal strength-based cooperative localization has gained significant interest due to its low complexity and cost-effectiveness. The conventional techniques often use Taylor expansion to address the non-convex, non-linear, and discontinuous characteristics of the maximum likelihood (ML) objective function. However, this results in a considerable residual error that exponentially grows with noise. To address this issue, we propose a cooperative (and non-cooperative) localization technique using received signal strength (RSS) measurements, named C-UA (and NC-UA), which employs a relative error-based estimator. We then use weighted non-linear least squares (NLS) to formulate a semidefinite programming (SDP) problem. C-UA and NC-CA can jointly estimate the location and transmit power of target nodes while considering the uncertainty in anchor nodes' locations. We also derive the Cramer-Rao lower bound (CRLB) involving unknown transmit power and anchor location uncertainty. We perform extensive outdoor real-world tests in an open field (640 m × 180 m), using 50 Bluetooth transceivers to collect RSS measurements. We record the location of each node using two devices: a real-time kinematic (RTK)-GPS system, providing centimeter-level accuracy, and a standard GPS device, offering meter-level accuracy. The RTK-GPS measurements are considered the true positions, while the standard GPS measurements, with lower precision, are used to represent the uncertainty in the locations. Through ex...