Affiliation:
1. Nanjing Forest Police College
2. Nanjing Normal University
Abstract
In self-mixing dual-frequency laser Doppler velocimetry, the
self-mixing Doppler frequency shift of the optical frequency
difference is a linear function of the velocity of an external dynamic
object; however, it is always ultralow for signal processing.
Therefore, an ultralow frequency extraction method based on artificial
neural networks (NNs) is presented because NNs can accurately create a
fitting function for a Doppler signal and extend the signal to the DC
value, increasing the signal length and sampling points without
yielding unnecessary influences on the Doppler frequency. We precisely
measured Doppler frequencies in the frequency domain with a low
sampling rate and calculated the velocities for a target with
longitudinal movements. Compared to time-domain extraction,
frequency-domain extraction can reflect the complete information of
the original Doppler signal. This feature potentially contributes to
the signal processing of velocimetry in practical engineering
applications.
Funder
Science and Technology Planned Projects
of the Ministry of Public Security
Fundamental Research Funds for the
Central Universities
“Qinglan Project” of Universities in
Jiangsu Province
Jiangsu Key Research and Development
Planned Projects
Subject
Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering
Cited by
2 articles.
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