A Parameterized Generalized Radon-Fourier Transform-Based Method for Asteroid Detection Using Ground-Based Radar

Yinzi Wang, Gen Li*, Zhe Li, Yufei Sun, Hanlin Liu, Zegang Ding

*Corresponding author for this work

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

Abstract

The Generalized Radon-Fourier Transform is a powerful algorithm designed to integrate echo energy within complex motion models. Traditionally, the approach has been to convert the echo energy integration challenge into a parameterized model matching problem, typically using polynomial models. However, when dealing with the intricate motion of asteroids, polynomial models can lead to issues related to high computational order and significant complexity. To address these challenges, this paper introduces an innovative method that employs orbital elements as a parameterized model, effectively lowering the matching order and simplifying computational demands. Simulation results demonstrate a marked improvement in integration outcomes when compared to traditional polynomial models.

Original languageEnglish
Title of host publicationIEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331515669
DOIs
Publication statusPublished - 2024
Event2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024 - Zhuhai, China
Duration: 22 Nov 202424 Nov 2024

Publication series

NameIEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

Conference

Conference2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
Country/TerritoryChina
CityZhuhai
Period22/11/2424/11/24

Keywords

  • generalized radon-fourier transform(GRFT)
  • parameteried model matching

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