Joint ego-motion estimation and multiple object tracking using automotive radar

None, None; None, None; None, None; None, None

Joint ego-motion estimation and multiple object tracking using automotive radar

Conference Paper (2025)

Author(s)

S. Yuan (TU Delft - Microwave Sensing, Signals & Systems)

T. Wang (Student TU Delft)

Alexander Yarovoy (TU Delft - Microwave Sensing, Signals & Systems)

F. Fioranelli (TU Delft - Microwave Sensing, Signals & Systems)

Microwave Sensing, Signals & Systems

DOI related publication

https://doi.org/10.23919/EuRAD65285.2025.11234138

Signal processing MIMO radar Ego-motion estimation Multiple object tracking

To reference this document use:

https://resolver.tudelft.nl/uuid:602f1b74-ed77-4ba5-9cc1-acbefd5e6fce

More Info

expand_more

Publication Year

2025

Language

English

Microwave Sensing, Signals & Systems

Bibliographical Note

Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en

Pages (from-to)

11-14

ISBN (print)

979-8-3315-3649-7

ISBN (electronic)

978-2-87487-083-5

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

The problem of joint ego-motion estimation and multiple object tracking (MOT) in automotive multiple-input and multiple-output (MIMO) radar has been studied. The 3D ego-motion estimation is performed based on phase changes of the raw signal caused by relative movement between objects and the radar, and the ego-motion-induced velocities are compared with the detected ones to label static vs moving objects. The static objects are used for ego-motion estimation again to improve the accuracy, while the moving objects are used for MOT. The performance of the algorithm has been studied on simulated data and evaluated using different tracking algorithms, proving the feasibility of this approach.

Files

Joint_ego-motion_estimation_an... (pdf)

(pdf | 1.02 Mb)

License info not available

File under embargo until 17-05-2026