| Paper ID | SS-12.5 |
| Paper Title |
Extended Object Tracking with Automotive Radar Using B-Spline Chained Ellipses Model |
| Authors |
Gang Yao, University of Connecticut, United States; Pu Wang, Karl Berntorp, Hassan Mansour, Petros Boufounos, Philip Orlik, Mitsubishi Electric Research Laboratories (MERL), United States |
| Session | SS-12: Recent Advances in mmWave Radar Sensing for Autonomous Vehicles |
| Location | Gather.Town |
| Session Time: | Thursday, 10 June, 15:30 - 16:15 |
| Presentation Time: | Thursday, 10 June, 15:30 - 16:15 |
| Presentation |
Poster
|
| Topic |
Special Sessions: Recent Advances in mmWave Radar Sensing for Autonomous Vehicles |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
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. |
