Adaptive Displacement Calibration Strategies for Field Structural Health Monitoring Based on Doppler Radars

Davi V.Q. Rodrigues, Delong Zuo, Ziyan Tang, Jing Wang, Changzhan Gu, Changzhi Li

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

This article presents two displacement calibration algorithms for Doppler radar demodulated data, which contribute to accurate monitoring of small vibrations even when the conventional arctangent demodulated displacement exhibits abrupt jumps. The field structural health monitoring of a traffic signal support structure was carried out by a 5.8-GHz Doppler radar to verify the effectiveness of each algorithm. The radar sensor captures and downconverts the microwave signal, which is phase modulated by the mast arm motion after being reflected on the ground. When conventional nonlinear phase demodulation is employed to retrieve the mast arm displacement from the Doppler radar baseband responses, sudden jumps are encountered in the displacement measurement. Two novel algorithms, referred to as the adaptive low-pass filtering algorithm (ALFA) and the adaptive joint signal processing algorithm (AJSPA), respectively, are suggested to eliminate jumps in phase-demodulated Doppler radar data. These strategies are compared in terms of accuracy and computational cost. The simulated and experimental results are provided to validate the proposed techniques. The presented methods can have wide applications in radar-based vibration monitoring.

Original languageEnglish
Article number9049408
Pages (from-to)7813-7824
Number of pages12
JournalIEEE Transactions on Instrumentation and Measurement
Volume69
Issue number10
DOIs
StatePublished - Oct 2020

Keywords

  • Displacement measurement
  • Doppler radar
  • nonlinear phase demodulation
  • remote sensing
  • structural health monitoring (SHM)

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