4 papers · 1 filter
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…
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…