Extended Object Tracking With Automotive Radar Using B-Spline Chained Ellipses Model

This paper introduces a B-spline chained ellipses model representation for extended object tracking (EOT) using high-resolution automotive radar measurements. With offline automotive radar training datasets, the proposed model parameters are learned using the expectation-maximization (EM) algorithm....

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Bibliographic Details
Main Authors: Yao, G., Wang, P., Berntorp, K., Mansour, H., Boufounos, P., Orlik, P. V.
Format: Conference Proceeding
Language:English
Subjects:
automotive radar
B-spline
Extended object tracking
Numerical models
PMHT
Radar
Radar measurements
Radar tracking
random matrix model
Signal processing algorithms
Training
Transforms
unscented transform
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Description
Summary:This paper introduces a B-spline chained ellipses model representation for extended object tracking (EOT) using high-resolution automotive radar measurements. With offline automotive radar training datasets, the proposed model parameters are learned using the expectation-maximization (EM) algorithm. Then the probabilistic multi-hypothesis tracking (PMHT) along with the unscented transform (UT) is proposed to deal with the nonlinear forward-warping coordinate transformation, the measurement-to-ellipsis association, and the state update step. Numerical validation is provided to verify the effectiveness of the proposed EOT framework with automotive radar measurements.
ISSN:2379-190X
DOI:10.1109/ICASSP39728.2021.9415080