TY - GEN
T1 - A Parameterized Generalized Radon-Fourier Transform-Based Method for Asteroid Detection Using Ground-Based Radar
AU - Wang, Yinzi
AU - Li, Gen
AU - Li, Zhe
AU - Sun, Yufei
AU - Liu, Hanlin
AU - Ding, Zegang
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - generalized radon-fourier transform(GRFT)
KW - parameteried model matching
UR - http://www.scopus.com/inward/record.url?scp=86000021184&partnerID=8YFLogxK
U2 - 10.1109/ICSIDP62679.2024.10867930
DO - 10.1109/ICSIDP62679.2024.10867930
M3 - Conference contribution
AN - SCOPUS:86000021184
T3 - IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
BT - IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
Y2 - 22 November 2024 through 24 November 2024
ER -