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Found 8 papers, 1 papers with code
Few-Shot Learning with Uncertainty-based Quadruplet Selection for Interference Classification in GNSS Data
Jamming devices pose a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning.
Velocity-Based Channel Charting with Spatial Distribution Map Matching
However, current channel-charting approaches lag behind fingerprinting in their positioning accuracy and still require reference samples for localization, regular data recording and labeling to keep the models up to date.
Indoor Localization with Robust Global Channel Charting: A Time-Distance-Based Approach
While CC has shown promising results in modelling the geometry of the radio environment, a deeper insight into CC for localization using multi-anchor large-bandwidth measurements is still pending.
Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression
We show accuracy improvements for the APR-RPR task and for the RPR-RPR task for aerial vehicles and hand-held devices.
Towards Realistic Statistical Channel Models For Positioning: Evaluating the Impact of Early Clusters
Based on our measurement and simulation results, we propose a model for incorporating the signal reflection by obstacles in the vicinity of transmitter or receiver, so that the outcome of the model corresponds to the measurement made in such scenario.
Complementary Semi-Deterministic Clusters for Realistic Statistical Channel Models for Positioning
The models that capture the physical effects observed in a realistic deployment scenario are essential for assessing the potential benefits of enhancements in positioning methods.
Position Tracking using Likelihood Modeling of Channel Features with Gaussian Processes
We propose a novel localization framework that adapts well to sparse datasets that only contain CMs of specific areas within the environment with strong multipath propagation.
ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization
Visual Odometry (VO) accumulates a positional drift in long-term robot navigation tasks.
