Distributed Algorithm for Cooperative Joint Localization and Tracking Using Multiple-Input Multiple-Output Radars

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 to derive an iterative algorithm. The obtained algorithm features a small communication overhead that scales linearly with the number of radars in the system. The proposed algorithm shows good estimation accuracy in two simulated scenarios even below 0 dB signal to noise ratio. In both cases the ground truth falls within the 95 % confidence interval of the estimated posterior for the majority of the track.

Authors

Institutions

Publication Details

Published
2025-05-03
DOI
https://doi.org/10.1109/radar52380.2025.11031863
Citations
1
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
4.99
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Distributed Algorithm for Cooperative Joint Localization and Tracking Using Multiple-Input Multiple-Output Radars

Troels Pedersen, Anders Malthe Westerkam, Morten Sall Jensen, Mikkel Sebastian Lundsgaard Brøndt et al.
1 citations
Radar Systems and Signal Processing
4.99
article

Distributed Algorithm for Cooperative Joint Localization and Tracking Using Multiple-Input Multiple-Output Radars

Troels Pedersen, Anders Malthe Westerkam, Morten Sall Jensen, Mikkel Sebastian Lundsgaard Brøndt, Astrid Holm Filtenborg Kitchen
article en
1 citations

Abstract

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 to derive an iterative algorithm. The obtained algorithm features a small communication overhead that scales linearly with the number of radars in the system. The proposed algorithm shows good estimation accuracy in two simulated scenarios even below 0 dB signal to noise ratio. In both cases the ground truth falls within the 95 % confidence interval of the estimated posterior for the majority of the track.

Aalborg University (DK)
Openalex Percentile: Top 6%
Radar Systems and Signal Processing
4.99
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.