293 citations · 604 across the 10 of their papers we have counts for
12 papers
PMBM-based SLAM Filters in 5G mmWave Vehicular Networks
Hyowon Kim, Karl Granström, Lennart Svensson +2
Radio-based vehicular simultaneous localization and mapping (SLAM) aims to localize vehicles while mapping the landmarks in the environment. We propose a sequence of three Poisson…
Gaussian implementation of the multi-Bernoulli mixture filter
Ángel F. García-Fernández, Yuxuan Xia, Karl Granström +2
This paper presents the Gaussian implementation of the multi-Bernoulli mixture (MBM) filter. The MBM filter provides the filtering (multi-target) density for the standard dynamic a…
5G mmWave Cooperative Positioning and Mapping using Multi-Model PHD Filter and Map Fusion
Hyowon Kim, Karl Granström, Lin Gao +3
5G millimeter wave (mmWave) signals can enable accurate positioning in vehicular networks when the base station and vehicles are equipped with large antenna arrays. However, radio-…
Bayesian Smoothing for the Extended Object Random Matrix Model
Karl Granström, Jakob Bramstång
The random matrix model is popular in extended object tracking, due to its relative simplicity and versatility. In this model, the extended object state consists of a kinematic vec…
Decentralized Poisson Multi-Bernoulli Filtering for Vehicle Tracking
Markus Fröhle, Karl Granström, Henk Wymeersch
A decentralized Poisson multi-Bernoulli filter is proposed to track multiple vehicles using multiple high-resolution sensors. Independent filters estimate the vehicles' presence, s…
Poisson multi-Bernoulli mixture trackers: continuity through random finite sets of trajectories
Karl Granström, Lennart Svensson, Yuxuan Xia +2
The Poisson multi-Bernoulli mixture (PMBM) is an unlabelled multi-target distribution for which the prediction and update are closed. It has a Poisson birth process, and new Bernou…
An Implementation of the Poisson Multi-Bernoulli Mixture Trajectory Filter via Dual Decomposition
Yuxuan Xia, Karl Granström, Lennart Svensson +1
This paper proposes an efficient implementation of the Poisson multi-Bernoulli mixture (PMBM) trajectory filter. The proposed implementation performs track-oriented N-scan pruning…
Poisson Multi-Bernoulli Mapping Using Gibbs Sampling
Maryam Fatemi, Karl Granström, Lennart Svensson +2
This paper addresses the mapping problem. Using a conjugate prior form, we derive the exact theoretical batch multi-object posterior density of the map given a set of measurements.…
Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and PMBM Filtering
Samuel Scheidegger, Joachim Benjaminsson, Emil Rosenberg +2
Monocular cameras are one of the most commonly used sensors in the automotive industry for autonomous vehicles. One major drawback using a monocular camera is that it only makes ob…
Multisensor Poisson Multi-Bernoulli Filter for Joint Target-Sensor State Tracking
Markus Fröhle, Christopher Lindberg, Karl Granström +1
In a typical multitarget tracking (MTT) scenario, the sensor state is either assumed known, or tracking is performed in the sensor's (relative) coordinate frame. This assumption do…
Poisson multi-Bernoulli mixture filter: direct derivation and implementation
Ángel F. García-Fernández, Jason L. Williams, Karl Granström +1
We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multi-target tracking with the standard point target measurements without using probability generat…
Poisson multi-Bernoulli conjugate prior for multiple extended object filtering
Karl Granstrom, Maryam Fatemi, Lennart Svensson
This paper presents a Poisson multi-Bernoulli mixture (PMBM) conjugate prior for multiple extended object filtering. A Poisson point process is used to describe the existence of ye…