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Decoupling and Parameter Extraction Methods for Conical Micro-Motion Object Based on FMCW Lidar.

Zhen Yang1, Yufan Yang1, Manguo Liu2

  • 1Department of Optoelectronic Information Science and Technology, Harbin Institute of Technology, Harbin 150080, China.

Sensors (Basel, Switzerland)
|March 28, 2024
PubMed
Summary

This study introduces a novel method for extracting parameters of micro-motion cones using Frequency Modulated Continuous Wave (FMCW) lidar. The technique combines range profiles and micro-Doppler time-frequency analysis for accurate structure and motion parameter retrieval.

Keywords:
FMCW lidardecouplinglaser micro-Dopplermicro-motionrange profile

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Area of Science:

  • * Radar signal processing and target recognition.
  • * Applied physics and optical engineering.

Background:

  • * Micro-Doppler time-frequency analysis is crucial for conical micro-motion object parameter extraction.
  • * Frequency modulation of lidar echoes by micro-motion causes parameter coupling, complicating analysis.
  • * Existing methods struggle with accurate separation of structure and micro-motion parameters for cones.

Purpose of the Study:

  • * To develop a new method for accurately decoupling and extracting structure and micro-motion parameters of conical objects.
  • * To enhance the accuracy and richness of information obtained from micro-Doppler analysis.
  • * To provide a foundation for improved classification and recognition of micro-motion cones.

Main Methods:

  • * Utilized Frequency Modulated Continuous Wave (FMCW) lidar for simulating micro-motion cone range profiles.
  • * Performed quantitative analysis on edge features of range profiles and micro-Doppler time-frequency spectra.
  • * Implemented a proposed decoupling parameter extraction method.

Main Results:

  • * Successfully extracted cone height, base radius, precession angle, spin frequency, and gravity center height.
  • * Achieved accurate extraction within lidar line-of-sight angles from 20° to 65°.
  • * Demonstrated an average absolute percentage error below 10%.

Conclusions:

  • * The proposed method effectively decouples and extracts cone parameters, surpassing traditional time-frequency analysis.
  • * This approach enriches detection information and improves parameter extraction accuracy for micro-motion cones.
  • * Establishes a novel technical foundation for laser micro-Doppler detection and accurate target recognition.