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Proceedings Paper

Inversion method of actual machined surface parameters in absolute distance measurement without cooperation target laser
Author(s): Huirong Tao
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Paper Abstract

In the absolute distance measurement of the non-cooperative target laser, the backscattering characteristics of the long-distance, real-machined surface are complex, and the parameters such as the incident azimuth angle, the incident angle, the surface texture, and the roughness are all have an impact to the real surface backscatter field distribution. Usually in the long distance, the distance measurement fails because the backscattering energy is weak. Therefore, the above parameters directly affect the absolute ranging range and accuracy, which is also an important bottleneck restricting the development of absolute ranging technology without cooperation targets. Aiming at this problem, a method to improve the range of actual machining surface ranging is proposed. According to the data collected by the ranging system, a multidimensional parameter inversion model of machining surface is constructed. This method can reverse the parameters such as the incident azimuth, the incident angle, the texture of the surface to be tested, the roughness and the processing method. It is verified by experiments that the actual surface processing method can be accurately distinguished under the inversion method, and the accuracy of the incident azimuth angle and the measured surface roughness inversion is also high, and the relative inversion errors are 1.20% and 1.01%, respectively. It is verified by experiments that the inversion of surface parameters greatly broadens the range of absolute distance measurement of non-cooperative target laser.

Paper Details

Date Published: 18 December 2019
PDF: 6 pages
Proc. SPIE 11338, AOPC 2019: Optical Sensing and Imaging Technology, 113382N (18 December 2019); doi: 10.1117/12.2547710
Show Author Affiliations
Huirong Tao, Tianjin Vocational Institute (China)

Published in SPIE Proceedings Vol. 11338:
AOPC 2019: Optical Sensing and Imaging Technology
John E. Greivenkamp; Jun Tanida; Yadong Jiang; HaiMei Gong; Jin Lu; Dong Liu, Editor(s)

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