7 papers
A Variational Message Passing Framework for Multi-Sensor Multi-Object Tracking using Raw Radar Signals
Anders Malthe Westerkam, Jakob Möderl, Erik Leitinger +1
The growing proliferation of unmanned aerial vehicles (UAVs) poses major challenges for reliable airspace surveillance, as drones are typically small, have low radar cross-sections…
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…
Variational Bayesian Estimation of Low Earth Orbits for Satellite Communication
Anders Malthe Westerkam, Amélia Struyf, Dimitri Lederer +2
Low-earth-orbit (LEO) satellite communication systems that use millimeter-wave frequencies rely on large antenna arrays with hybrid analog-digital architectures for rapid beam stee…
Second-Order Characterization of Micro Doppler Radar Signatures of Drone Swarms
Anders Malthe Westerkam, Alba Spliid Damkjær, Rasmus Erik Villadsen +2
We investigate the second-order characteristics of the radar return signal from a swarm of rotor drones. We consider the case of a swarm of identical drones, with each a number of…
Clutter Tracking using Variational Message Passing
Anders Malthe Westerkam, Troels Pedersen
We propose a message passing algorithm for tracking of clutter signals in MIMO radar. The method exploits basis expansion to linearise the signal model, to enable mean field approa…
Distributed Algorithm for Cooperative Joint Localization and Tracking Using Multiple-Input Multiple-Output Radars
Astrid Holm Filtenborg Kitchen, Mikkel Sebastian Lundsgaard Brøndt, Marie Saugstrup Jensen +2
We propose a distributed joint localization and tracking algorithm using a message passing framework, for multiple-input multiple-output radars. We employ the mean field approach t…