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http://dx.doi.org/10.3807/JOSK.2015.19.1.095

Approach of Self-mixing Interferometry Based on Particle Swarm Optimization for Absolute Distance Estimation  

Li, Li (State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University)
Li, Xingfei (State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University)
Kou, Ke (State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University)
Wu, Tengfei (State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University)
Publication Information
Journal of the Optical Society of Korea / v.19, no.1, 2015 , pp. 95-101 More about this Journal
Abstract
To accurately extract absolute distance information from a self-mixing interferometry (SMI) signal, in this paper we propose an approach based on a particle swarm optimization (PSO) algorithm instead of frequency estimation for absolute distance. The algorithm is utilized to search for the global minimum of the fitness function that is established from the self-mixing signal to find out the actual distance. A resolution superior to $25{\mu}m$ in the range from 3 to 20 cm is obtained by experimental measurement, and the results demonstrate the superiority of the proposed approach in comparison with interpolated FFT. The influence of different external feedback strength parameters and different inertia weights in the algorithm is discussed as well.
Keywords
Self-mixing interferometry; Particle swarm optimization; Absolute distance estimation;
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Times Cited By KSCI : 1  (Citation Analysis)
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