5 papers
NeRC: Neural Ranging Correction through Differentiable Moving Horizon Location Estimation
Xu Weng, K. V. Ling, Haochen Liu +2
GNSS localization using everyday mobile devices is challenging in urban environments, as ranging errors caused by the complex propagation of satellite signals and low-quality onboa…
Receding Horizon Recursive Location Estimation
Xu Weng, K. V. Ling, Ling Zhao
This paper presents a recursive solution to the receding or moving horizon estimation (MHE) problem for nonlinear time-variant systems. We provide the conditions under which the re…
Towards End-to-End GPS Localization with Neural Pseudorange Correction
Xu Weng, KV Ling, Haochen Liu +1
The pseudorange error is one of the root causes of localization inaccuracy in GPS. Previous data-driven methods regress and eliminate pseudorange errors using handcrafted intermedi…
Localization with Noisy Android Raw GNSS Measurements
Xu Weng, Keck Voon Ling
Android raw Global Navigation Satellite System (GNSS) measurements are expected to bring smartphones power to take on demanding localization tasks that are traditionally performed…
PrNet: A Neural Network for Correcting Pseudoranges to Improve Positioning with Android Raw GNSS Measurements
Xu Weng, Keck Voon Ling, Haochen Liu
We present a neural network for mitigating biased errors in pseudoranges to improve localization performance with data collected from mobile phones. A satellite-wise Multilayer Per…