A MIMO Radar Angle Tracking Method based on Adaptive Parallel Factor Decomposition

Jiangwen Zhou, Qing Liu, Jian Xie, Yanyun Gong, Ling Wang

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

Abstract

To address the problem of high computational complexity in the existing Direction of Arrival (DOA) and Direction of Departure (DOD) tracking algorithms for Multiple Input Multiple Output (MIMO) radar systems, this paper proposes a joint DOA-DOD tracking algorithm for moving targets utilizing the adaptive parallel factor (PARAFAC) decomposition of the multidimensional received data. By establishing a third-order measurement tensor signal model, the proposed adaptive PARAFAC tracking algorithm firstly estimates both the transmit and receive array manifolds jointly, and further tracks the DOD and DOA parameters of the moving targets. According to the simulation results, this approach effectively reduces the computational complexity and improves the real-time performance.

Original languageEnglish
Title of host publication2024 IEEE INC-USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), INC-USNC-URSI 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages236-237
Number of pages2
ISBN (Electronic)9789463968119
DOIs
StatePublished - 2024
Event2024 IEEE INC-USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), INC-USNC-URSI 2024 - Florence, Italy
Duration: 14 Jul 202419 Jul 2024

Publication series

Name2024 IEEE INC-USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), INC-USNC-URSI 2024 - Proceedings

Conference

Conference2024 IEEE INC-USNC-URSI Radio Science Meeting (Joint with AP-S Symposium), INC-USNC-URSI 2024
Country/TerritoryItaly
CityFlorence
Period14/07/2419/07/24

Fingerprint

Dive into the research topics of 'A MIMO Radar Angle Tracking Method based on Adaptive Parallel Factor Decomposition'. Together they form a unique fingerprint.

Cite this