Abstract
This paper focuses on developing an algorithm for tracking closely-spaced road vehicles using a low-density flash lidar. Low-density flash lidars have poor spatial resolution that can causes detections from multiple targets to be merged/unresolved when the targets being tracked are closely spaced. Previous solutions for target tracking with unresolved measurements have typically focused on tracking with exactly two targets with a radar. In this paper, a novel solution based on Probability Density Function (PDF) truncation of the target states is presented to handle the unresolved measurement problem with more than two road targets. The solution proposed can work with a computationally inexpensive data association algorithm and requires no sensor modeling. For illustration, the proposed algorithm is evaluated using simulations for a three target tracking scenario in MATLAB, and the results show that the proposed algorithm can reliably maintain tracks of multiple targets even when the detections are unresolved.
Original language | English (US) |
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Title of host publication | 2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 661-666 |
Number of pages | 6 |
ISBN (Electronic) | 9781665441391 |
DOIs | |
State | Published - Jul 12 2021 |
Event | 2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2021 - Delft, Netherlands Duration: Jul 12 2021 → Jul 16 2021 |
Publication series
Name | 2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) |
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Conference
Conference | 2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2021 |
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Country/Territory | Netherlands |
City | Delft |
Period | 7/12/21 → 7/16/21 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
Keywords
- Flash lidar
- Kalman filtering
- PDF Truncation
- Target Tracking
- Unresolved Measurements