Paper
15 October 2012 Second-order moment estimation of pointing errors in laser pointing system using return photons
Lei Zhou, Ge Ren, Yi Tan
Author Affiliations +
Proceedings Volume 8420, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical System Technologies for Manufacturing and Testing; 842014 (2012) https://doi.org/10.1117/12.971586
Event: 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies (AOMATT 2012), 2012, Xiamen, China
Abstract
Boresight and jitter that cause energy loss and decline of the system performance are two fundamental pointing errors for a laser pointing system. Based on the statistics of the return photons reflected from target and estimation of the pointing errors, a second-order moment estimation algorithm is proposed. This algorithm that is the expansion of the Key-rate method can estimate boresight and jitter simultaneously. In this paper, a laser pointing system model based on a Gaussian far-field irradiance profile and a Gaussian beam jitter is setup, a laboratory experiment is performed, and the simulation and experimental data is processed by this estimator. The results demonstrate that the performance of the second-order moment estimation is excellent and the performance improves with the increasing number of shots. What’s more, the further study finds that the experimental results agree well with the simulation results.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lei Zhou, Ge Ren, and Yi Tan "Second-order moment estimation of pointing errors in laser pointing system using return photons", Proc. SPIE 8420, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical System Technologies for Manufacturing and Testing, 842014 (15 October 2012); https://doi.org/10.1117/12.971586
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KEYWORDS
Error analysis

Statistical analysis

Photons

Laser systems engineering

Computer simulations

Monte Carlo methods

Data modeling

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