8 papers
Bernoulli Filtering for Multi-Sensor Tracking with Thresholded Measurements
Gustav Zetterqvist, Fredrik Gustafsson, Gustaf Hendeby
Target tracking is challenging when sensor detection thresholds cause state-dependent missed detections, particularly in multi-sensor scenarios with clutter and uncertain target ex…
Matrix-Valued Measures and Wishart Statistics for Target Tracking Applications
Robin Forsling, Simon J. Julier, Gustaf Hendeby
Ensuring sufficiently accurate models is crucial in target tracking systems. If the assumed models deviate too much from the truth, the tracking performance might be severely degra…
An Observability-Constrained Magnetic Field-Aided Inertial Navigation System -- Extended Version
Chuan Huang, Gustaf Hendeby, Isaac Skog
Maintaining consistent uncertainty estimates in localization systems is crucial as the perceived uncertainty commonly affects high-level system components, such as control or decis…
Adaptive Basis Function Selection for Computationally Efficient Predictions
Anton Kullberg, Frida Viset, Isaac Skog +1
Basis Function (BF) expansions are a cornerstone of any engineer's toolbox for computational function approximation which shares connections with both neural networks and Gaussian…
Joint State and Parameter Estimation Using the Partial Errors-in-Variables Principle
Peng Liu, Kailai Li, Gustaf Hendeby +1
This letter proposes a new method for joint state and parameter estimation in uncertain dynamical systems. We exploit the partial errors-in-variables (PEIV) principle and formulate…
Bayesian Simultaneous Localization and Multi-Lane Tracking Using Onboard Sensors and a SD Map
Yuxuan Xia, Erik Stenborg, Junsheng Fu +1
High-definition map with accurate lane-level information is crucial for autonomous driving, but the creation of these maps is a resource-intensive process. To this end, we present…