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Multi-Dimensional Information Association of Vehicular MIMO Radar Based on Tracking Algorithm

  • Jiawei Huo
  • , Kun Hu
  • , Yue Song
  • , Zhongyu Li
  • , Junjie Wu
  • , Hang Ren
  • , Huazeng Deng
  • University of Electronic Science and Technology of China
  • Zoox Inc.

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the application of vehicular MIMO (Multiple Input Multiple Output) radar, it is particularly important to measure and associate the position and velocity of targets. However, traditional methods like 3D-FFT have low angular resolution, and velocity ambiguity resolution is required. Combined with Super-resolution DOA (Direction Of Arrival) algorithm, we propose a multi-dimensional information association method based on target tracking, which uses the labeled GM-PHD (Gaussian Mixture Probability Hypothesis Density) algorithm. This method simultaneously completes the association task about position and velocity and the tracking task, and does not require an additional step on velocity ambiguity resolution. Finally, we use experimental data to verify the effectiveness of the algorithm.

Original languageEnglish
Title of host publicationIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4816-4819
Number of pages4
ISBN (Electronic)9798350320107
DOIs
StatePublished - 2023
Externally publishedYes
Event2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, United States
Duration: 16 Jul 202321 Jul 2023

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2023-July

Conference

Conference2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Country/TerritoryUnited States
CityPasadena
Period16/07/2321/07/23

Keywords

  • GM-PHD
  • MIMO radar
  • Super-resolution DOA
  • multi-dimensional information association

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