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Correlation coefficient local capping REMD adaptive filtering method for laser interference signal.

Junfeng Wu¹, Hanyu Chen¹, Xu Li¹

¹Key Laboratory of Space Photoelectric Detection and Perception of Ministry of Industry and Information Technology, The College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.

|January 21, 2022

Summary

This summary is machine-generated.

A novel robust empirical mode decomposition filter algorithm effectively reduces noise in Laser Doppler Interference (LDI) signals. This method enhances displacement information extraction and improves experimental frequency separation performance.

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Area of Science:

Optoelectronics
Signal Processing
Metrology

Background:

Laser Doppler Interference (LDI) signals are susceptible to high-frequency noise, complicating accurate displacement measurement.
Existing noise reduction techniques may not sufficiently preserve the integrity of the LDI signal for precise reconstruction.

Purpose of the Study:

To develop and validate a robust noise reduction algorithm for LDI signals.
To enhance the accuracy of displacement information reconstruction from noisy LDI data.
To improve the frequency separation capabilities in experimental setups using LDI sensors.

Main Methods:

Implementation of a correlation coefficient local capping robust empirical mode decomposition (REMD) filter.
Application of the REMDL filter to Laser Doppler Interference (LDI) laser sensor signals.
Experimental validation using Hilbert phase unwrapping for displacement reconstruction.

Main Results:

The REMDL algorithm effectively removes high-frequency noise from LDI signals.
The method facilitates easier extraction of useful information from the processed signals.
Experimental validation demonstrated improved frequency separation and robustness against noise interference.

Conclusions:

The proposed correlation coefficient local capping REMDL filter offers a robust solution for noise reduction in LDI signals.
This algorithm significantly enhances the quality of reconstructed displacement information.
The method shows practical utility in improving the performance of LDI-based experimental measurements.