Mr. Zhenguo Yan Profile

Zhenguo Yan

at National University of Defense Technology

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Proceedings Article | 6 May 2024 Paper

Target positioning based on AIS data and optical remote sensing image fusion

Xueyang Wang, Xin Song, Zhenguo Yan, Yun Cheng

Proceedings Volume 13107, 1310729 (2024) https://doi.org/10.1117/12.3029102

KEYWORDS: Image fusion, Data fusion, Remote sensing, Calibration, Ocean optics, Global Positioning System

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For ocean remote sensing, target positioning over large areas of sea surface can be challenging, and traditional methods that rely on control points data may not be applicable in such cases. AIS data are commonly used as auxiliary data source of ocean remote sensing, which contains a wealth of attribute information of target. High-precision position information for a large number of targets is provided by the AIS equipped with differential GPS. AIS can be used as dynamic control points on the sea surface to contribute to target positioning in remote sensing image, meeting the on-orbit real-time positioning requirements of ocean remote sensing. This paper proposes a method for on-orbit target positioning and identification through the data fusion of optical image and AIS data. Firstly, the target position information provided by AIS is the broadcasted position over a period of time, while remote sensing image provide the instantaneous captured position. Therefore, it is necessary to calibrate the two types of data in terms of time and space. Then, the grid matching algorithm is used to establish the corresponding relationships between the same targets from the two different datasets, thereby achieving data fusion. Finally, target positioning is achieved over large areas of sea surface. In addition, the identification of target can also be facilitated by remote sensing image with the aid of AIS data, enabling precise positioning of abnormal target while obtaining their image information. In this paper, 5-meter resolution Jilin-1 satellite image and AIS data are used as data sources. The results show that, compared with the original data, the positioning error values calculated by this method are between 5-20 meters, with a reduction of over 70% in the RMSE value.

Proceedings Article | 12 March 2020 Paper

An adaptive window motion blurred star restoration based on energy equalization

Fengqi Jiang, Xin Song, Zhenguo Yan

Proceedings Volume 11438, 114380H (2020) https://doi.org/10.1117/12.2543281

KEYWORDS: Stars, Star sensors, Motion models, Sensors, Image restoration, Imaging systems, Satellites, Gyroscopes, Image processing, Motion estimation

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The accuracy of star centroid extraction and identified star number is both crucial features for star sensor precision. Motion blur and fracture are introduced when star sensor works under high dynamic conditions, which affect the accuracy of star centroid extraction and further reduce the precision of the star sensor. To improve the precision of star sensor, this paper proposes an adaptive window star map restoration method based on energy equalization. The local degradation function is estimated for the star point energy distribution region, and dynamic star map simulation and restoration are performed. The simulation process is divided into three steps. Firstly, establish the motion trajectory of the star point centroid in the detector plane during the exposure time, according to the trailing trajectory size and direction adaptive selection window. Secondly, accumulate the star image point energy in the adaptive window to achieve star point recovery, and finally the recovery effect was evaluated by star extraction results.

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