5 papers
Bayesian Self-Calibration and Parametric Channel Estimation for 6G Antenna Arrays
Patrick Hödl, Jakob Möderl, Erik Leitinger +1
Accurate channel estimation is essential for both high-rate communication and high-precision sensing in 6G wireless systems. However, a major performance limitation arises from cal…
A Block-Sparse Bayesian Learning Algorithm with Dictionary Parameter Estimation for Multi-Sensor Data Fusion
Jakob Möderl, Anders Malte Westerkam, Alexander Venus +1
We propose an sparse Bayesian learning (SBL)-based method that leverages group sparsity and multiple parameterized dictionaries to detect the relevant dictionary entries and estima…
General Pruning Criteria for Fast SBL
Jakob Möderl, Erik Leitinger, Bernard Henri Fleury
Sparse Bayesian learning (SBL) associates to each weight in the underlying linear model a hyperparameter by assuming that each weight is Gaussian distributed with zero mean and pre…
Fast Variational Block-Sparse Bayesian Learning
Jakob Möderl, Erik Leitinger, Bernard H. Fleury +2
We propose a variational Bayesian (VB) implementation of block-sparse Bayesian learning (BSBL) to compute proxy probability density functions (PDFs) that approximate the posterior…
Variational Message Passing-based Multiobject Tracking for MIMO-Radars using Raw Sensor Signals
Anders Malthe Westerkam, Jakob Möderl, Erik Leitinger +1
In this paper, we propose a direct multiobject tracking (MOT) approach for MIMO-radar signals that operates on raw sensor data via variational message passing (VMP). Unlike classic…