A Novel Angle-Delay-Doppler Estimation Scheme for AFDM-ISAC System in Mixed Near-field and Far-field Scenarios

Yirui Luo, Yong Liang Guan, Yao Ge, G. David Gonzalez, Chau Yuen

Research output: Contribution to journalArticlepeer-review

Abstract

The recently proposed multi-chirp waveform, affine frequency division multiplexing (AFDM), is considered as a potential candidate for integrated sensing and communication (ISAC). However, acquiring accurate target sensing parameter information becomes challenging due to fractional delay and Doppler shift occurrence, as well as effects introduced by the coexistence of near-field (NF) and far-field (FF) targets associated with large-scale antenna systems. In this paper, we propose a novel angle-delay-Doppler estimation scheme for AFDM-ISAC system in mixed NF and FF scenarios. Specifically, we model the received ISAC signals as a third-order tensor that admits a low-rank CANDECOMP/PARAFAC (CP) format. By employing the Vandermonde nature of the factor matrix and the spatial smoothing technique, we develop a structured CP decomposition method that guarantees the condition for uniqueness. We further propose a low-complexity estimation scheme to acquire target sensing parameters with fractional values, including angle of arrival/departure (AoA/AoD), delay and Doppler shift accurately. We also derive the Cramér-Rao Lower Bound (CRLB) as a benchmark and analyze the complexity of our proposed scheme. Finally, simulation results are provided to demonstrate the effectiveness and superiority of our proposed scheme.

Original languageEnglish
JournalIEEE Internet of Things Journal
DOIs
Publication statusAccepted/In press - 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

ASJC Scopus Subject Areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

Keywords

  • AFDM
  • DAFT
  • high mobility
  • Internet of Everything (IoE)
  • ISAC
  • MIMO
  • mixed NF and FF sensing
  • tensor signal processing

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