Paper
24 November 2021 Study on Kalman dynamic prediction and feedback parameter optimization of laser tracking system
Jin Shi, Lijun Miao, Qinghua Xu, Xiaowu Shu, Shuangliang Che
Author Affiliations +
Proceedings Volume 12066, AOPC 2021: Micro-optics and MOEMS; 120661A (2021) https://doi.org/10.1117/12.2606602
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China
Abstract
Under the environment of MATLAB, a closed-loop feedback laser tracking system was established based on the dynamic prediction with Kalman filter and some other filtering processes. Different motion states of the tracked target are simulated to test the tracking performance. The following conclusions are obtained through simulations. After adding the dynamic prediction with Kalman filter, the tracking hysteresis can effectively be avoided when tracking the dynamic object. Taking advantage of the high frequency of PSD, the coordinate value can be read for several times in a feedback loop and then filtered to obtain a more accurate spot coordinate. Under static condition, the instability due to noise can be reduced through segmenting the feedback coefficient by distinguishing between the dynamic and static state of the object. According to the above designs, the results of the laser tracking system simulations show that the dynamic tracking performance is better than 100°/s, and static stability has an order of magnitude improvement than before.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jin Shi, Lijun Miao, Qinghua Xu, Xiaowu Shu, and Shuangliang Che "Study on Kalman dynamic prediction and feedback parameter optimization of laser tracking system", Proc. SPIE 12066, AOPC 2021: Micro-optics and MOEMS, 120661A (24 November 2021); https://doi.org/10.1117/12.2606602
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KEYWORDS
Filtering (signal processing)

Laser systems engineering

Digital filtering

Electronic filtering

Control systems

Metrology

Optical filters

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