Karl Granström
Karl Granström is a Postdoc in the Signal Processing group. Before staring at Chalmers he was a Postdoc at the University of Connecticut, where he worked together with Peter Willett and Yaakov Bar-Shalom. Karl received his PhD degree in Automatic Control in November 2012, and the Master of Science degree in Applied Physics and Electrical Engineering in May 2008, both from Linköping University. His research interests are within the fields of sensor fusion, robotics and machine learning.
Showing 47 publications
Poisson Multi-Bernoulli Approximations for Multiple Extended Object Filtering
Backward simulation for sets of trajectories
Decentralized Poisson Multi-Bernoulli Filtering for Vehicle Tracking
Poisson Multi-Bernoulli Mixture Conjugate Prior for Multiple Extended Target Filtering
5G mmWave Cooperative Positioning and Mapping Using Multi-Model PHD Filter and Map Fusion
Extended Object Tracking with Automotive Radar Using Learned Structural Measurement Model
Trajectory Poisson Multi-Bernoulli Filters
Low-Complexity 5G Slam with CKF-PHD Filter
Joint CKF-PHD Filter and Map Fusion for 5G Multi-cell SLAM
Spatiotemporal Constraints for Sets of Trajectories with Applications to PMBM Densities
Trajectory multi-Bernoulli filters for multi-target tracking based on sets of trajectories
Multiscan implementation of the trajectory poisson multi-Bernoulli mixture filter
Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories
Bayesian Smoothing for the Extended Object Random Matrix Model
Bayesian Extended Object Smoothing for the Random Matrix Model
Multisensor Poisson Multi-Bernoulli Filter for Joint Target-Sensor State Tracking
Gaussian implementation of the multi-Bernoulli mixture filter
An Implementation of the Poisson Multi-Bernoulli Mixture Trajectory Filter via Dual Decomposition
Tracking Initially Unresolved Thrusting Objects Using an Optical Sensor
Poisson Multi-Bernoulli Mixture Trackers: Continuity Through Random Finite Sets of Trajectories
Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and PMBM Filtering
Likelihood-Based Data Association for Extended Object Tracking Using Sampling Methods
Multiple Target Tracking With Uncertain Sensor State Applied To Autonomous Vehicle Data
Poisson Multi-Bernoulli Mixture Filter: Direct Derivation and Implementation
Pedestrian tracking using Velodyne data-Stochastic optimization for extended object tracking
Multiple Sensor Measurement Updates for the Extended Target Tracking Random Matrix Model
Guest editorial: Foreword to the special issue on extended object tracking
Poisson Multi-Bernoulli Mapping Using Gibbs Sampling
Tracking initially unresolved thrusting objects in 3D using a single stationary optical sensor
A fast implementation of the Labeled Multi-Bernoulli filter using gibbs sampling
Performance evaluation of multi-bernoulli conjugate priors for multi-target filtering
Converted measurements Bayesian extended target tracking applied to x-band marine radar data
Extended OBJECT TRACKING: Introduction, overview, and applications
Multistatic Bayesian Extended Target Tracking
Approximate Multi-Hypothesis Multi-Bernoulli Multi-Object Filtering Made Multi-Easy
Multiple sensor Bayesian extended target tracking fusion approaches using random matrices
Metrics for performance evaluation of elliptic extended object tracking methods
Gamma Gaussian inverse-Wishart Poisson multi-Bernoulli filter for extended target tracking
Poisson multi-Bernoulli filter for extended object tracking
Asymmetric Threat Modeling Using HMMs: Bernoulli Filtering and Detectability Analysis
Multiple Extended Target Tracking With Labeled Random Finite Sets
Poisson Multi-Bernoulli Radar Mapping Using Gibbs Sampling
Multi-Bernoulli Filtering for Initially Unresolved Targets in Clutter
Detectability prediction of hidden Markov models with cluttered observation sequences
Systematic Approach to IMM Mixing for Unequal Dimension States
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Showing 1 research projects
Deep multi-object tracking for ground truth trajectory estimation