7 papers
Multi-Sensor Fusion for Extended Object Tracking Exploiting Active and Passive Radio Signals
Hong Zhu, Alexander Venus, Erik Leitinger +1
Reliable and robust positioning of radio devices remains a challenging task due to multipath propagation, hardware impairments, and interference from other radio transmitters. A fr…
AI-enhanced Direct SLAM: A Principled Approach to Unsupervised Learning in Bayesian Inference
Alexander Venus, Benjamin Deutschmann, Alexander Fuchs +2
In this paper, we propose an artificial intelligence (AI)-enhanced hybrid simultaneous localization and mapping (SLAM) method that performs Bayesian inference directly on raw radio…
Simultaneous Source Separation, Synchronization, Localization and Mapping for 6G Systems
Alexander Venus, Erik Leitinger, Klaus Witrisal
Multipath-based simultaneous localization and mapping (MP-SLAM) is a promising approach for future 6G networks to jointly estimate the positions of transmitters and receivers toget…
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…
A Sigma Point-based Low Complexity Algorithm for Multipath-based SLAM in MIMO Systems
Anna Masiero, Alexander Venus, Erik Leitinger
Multipath-based simultaneous localization and mapping (MP-SLAM) is a promising approach in wireless networks to jointly obtain position information of transmitters/receivers and in…
Multi-Sensor Fusion of Active and Passive Measurements for Extended Object Tracking
Hong Zhu, Alexander Venus, Erik Leitinger +1
This paper addresses the challenge of achieving robust and reliable positioning of a radio device carried by an agent, in scenarios where direct line-of-sight (LOS) radio links are…