Dr. Zhonghong Bu Profile

Dr. Zhonghong Bu

at Xi'an Institute of Applied Optics

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Publications (2)

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Proceedings Article | 18 March 2024 Paper

Opto-mechanical dynamics optimization of electro-optical stabilized sighting system based on data driving

Qingqing Xu, Kaidi Wang, Zhonghong Bu, Feilin Lei, Jingyu Wan, Shaokang Yang

Proceedings Volume 13104, 131043M (2024) https://doi.org/10.1117/12.3023502

KEYWORDS: Vibration, Optical components, Finite element methods, Mirrors, Sensors, Matrices, Mathematical optimization, Data modeling, Reflection, Imaging systems

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Difference exists between modeling result of current electro-optical stabilized sighting system (EOSSS) and dynamics characteristics of actual structure. As a result, accurate description of optical performance of imaging system in vibration environment is relatively difficult, and then it seems complicated to improve anti-vibration characteristics efficiently through structure optimization. In order to solve these problems, a data-driven opto-mechanical dynamics optimization method is proposed in this paper. First, vibration mode and modal frequency of opto-mechanical structure are obtained through hammer hitting test and vibrator-exciting experiment. Oriented towards consistency of structural mode parameters and measured data, finite element model of EOSSS structure is acquired by iteration. Then, relationship among optical system performance and displacement of every optical element is described through optical sensitivity matrix. Linear optical model of imaging system is built and contribution of different optical element to line-of-sight (LOS) jitter is analyzed. After structural optimization of core optical elements, LOS jitter of EOSSS under vibration condition is obtained. Experimental results indicate that modal parameter error between proposed structural model and measured data is only 3.55%. Structural optimization of system based on the proposed model makes the LOS jitter of EOSSS under vibration environment reduce by 82.8%. Description of intrinsic characteristics of EOSSS structure is accurate by data-driven opto-mechanical dynamics optimization method. Therefore, structural optimization makes LOS stabilization improve dramatically under vibration condition.

Proceedings Article | 27 March 2022 Paper

A fusion imaging system with visible light camera and photon counting lidar

Libing Hou, Zhong Tao, Qingqing Xu, Longyang Kong, Bo Hu, Pingping Yun, Jing Wang, Zhonghong Bu

Proceedings Volume 12169, 121698T (2022) https://doi.org/10.1117/12.2625185

KEYWORDS: Imaging systems, Photon counting, Image fusion, 3D image processing, LIDAR, Image processing

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Photon counting lidar is a high-sensitivity laser active imaging method. It can obtain more three-dimensional point cloud data under the same size, weight and power consumption. Through the use of photon counting lidar and image fusion process, the electro-optical system, such as visible light and infrared camera, could generate grayscale images and videos with distance, position and other information of the targets. In this paper, a Fusion Imaging System with Visible Light Camera and Photon Counting Lidar was designed. Visible light image and high-resolution photon counting threedimensional point clouds could be obtained by the system. Fiber array coupled Geiger-APDs were used as the single photon detectors in the system to acquire three-dimensional information with two-dimensional scanner. A CMOS camera was used to acquire gray visible light image in the system. The time-correlated single photon counting (TCSPC) filter algorithm was used to process the single photon points in order to filter the noise signals and extract valid signals. The fusion processing algorithm of the imaging system was designed by using the direct linear transformation algorithm. The performance of the system was verified through experiments. The results show that the three-dimensional imaging range exceeds 1000m under the day light condition. The ranging accuracy of the system is 0.083m. Pixel-level fusion of visible light image and three-dimensional image could be realized at 1024×768 resolution, which effectively improves the detection and recognition capabilities of the system.

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