Inhalt anspringen

High-Resolution DOA Estimation Using Single-Snapshot Music for Automotive Radar with Mixed-ADC Allocations

Schnelle Fakten

  • Interne Autorenschaft

  • Weitere Publizierende

    Moritz Kahlert, Lifan Xu, Markus Gardill, Shunqiao Sun

  • Veröffentlichung

    • 2024
    • Band Proceedings of 2024 IEEE 13rd Sensor Array and Multichannel Signal Processing Workshop (SAM)
  • Fachgebiete

    • Kommunikations- und Informationstechnik
  • Forschungsschwerpunkte

    • Institut für Kommunikationstechnik (IKT)
  • Format

    Konferenzpaper

Zitat

T. Fei, M. Kahlert, L. Xu, M. Gardill, and S. Sun, “High-Resolution DOA Estimation Using Single-Snapshot Music for Automotive Radar with Mixed-ADC Allocations,” in Proceedings of 2024 IEEE 13rd Sensor Array and Multichannel Signal Processing Workshop (SAM), 2024, pp. 1–5.

Abstract

Fine direction of arrival (DOA) estimations are required for accurate target detections in automotive radar systems. To address this issue, most spectral estimation methods assume many snapshots of measurements. However, due to the dynamic nature of automotive scenarios, methods using multiple snapshots are impractical for DOA estimation in automotive radars. Furthermore, to relax the hardware requirements on modern automotive radar systems, mixed-analog-to-digital converter (ADC) allocations, i.e., the coexistence of 1-bit and high-resolution ADCs, have gained more attention recently. In this work, we introduce a high-resolution DOA estimation approach based on single-snapshot multiple signal classification (MUSIC) estimation and evaluate the performance with various ADC allocations. The results show that mixed-ADC allocations can perform comparably to high-resolution ADC allocations.

Erläuterungen und Hinweise

Diese Seite verwendet Cookies, um die Funktionalität der Webseite zu gewährleisten und statistische Daten zu erheben. Sie können der statistischen Erhebung über die Datenschutzeinstellungen widersprechen (Opt-Out).

Einstellungen (Öffnet in einem neuen Tab)