5 papers
Evaluation of An Indoor Localization Engine
Christophe Villien, Anne Frassati, Bruno Flament
Pedestrian Indoor localization based on modalities available in modern smartphones have been widely studied in literature and many of the specific challenges have been addressed. H…
A Novel Satellite Selection Algorithm Using LSTM Neural Networks For Single-epoch Localization
Ibrahim Sbeity, Christophe Villien, Christophe Combettes +3
This work presents a new approach for detection and exclusion (or de-weighting) of pseudo-range measurements from the Global Navigation Satellite System (GNSS) in order to improve…
RNN-Based GNSS Positioning using Satellite Measurement Features and Pseudorange Residuals
Ibrahim Sbeity, Christophe Villien, Benoît Denis +1
In the Global Navigation Satellite System (GNSS) context, the growing number of available satellites has lead to many challenges when it comes to choosing the most accurate pseudor…
Deep Learning with Partially Labeled Data for Radio Map Reconstruction
Alkesandra Malkova, Massih-Reza Amini, Benoit Denis +1
In this paper, we address the problem of Received Signal Strength map reconstruction based on location-dependent radio measurements and utilizing side knowledge about the local reg…
Self-Learning for Received Signal Strength Map Reconstruction with Neural Architecture Search
Aleksandra Malkova, Loic Pauletto, Christophe Villien +2
In this paper, we present a Neural Network (NN) model based on Neural Architecture Search (NAS) and self-learning for received signal strength (RSS) map reconstruction out of spars…