Accurate Star Centroid Detection for the Advanced Geosynchronous Radiation Imager of Fengyun-4A

Star observation can be used for the image navigation of certain instruments aboard the three-axis stabilized geostationary satellites. How to extract the accurate star centroids in the observed star images is one of the key problems. In this paper, a high precision star centroid detection method is proposed for the advanced geosynchronous radiation imager (AGRI) of Fengyun-4A (FY-4A), the first experimental satellite of the new generation of Chinese geostationary meteorological satellites FY-4 series. Different from star sensors which are deliberately defocused with relatively large star spot, AGRI is focused for the purpose of earth observation, making it challenging to extract accurate star centroids. To solve the problem, we take the advantage of continuous observing and improve the precision of star centroiding by trajectory fitting and energy response curve fitting. Extensive experiments have been performed on simulated star images and the actual observation data of AGRI aboard FY-4A over ten months in-orbit tests. Experimental results show that the proposed method can accurately extract star centroids with the error less than 0.3 pixels, laying a solid foundation for image navigation of FY-4A.

[1]  Zhiqing Zhang,et al.  Introducing the New Generation of Chinese Geostationary Weather Satellites, Fengyun-4 , 2017 .

[2]  Medeni Soysal,et al.  Performance of star centroiding methods under near-real sensor artifact simulation , 2015, 2015 7th International Conference on Recent Advances in Space Technologies (RAST).

[3]  Xiangqian Wu,et al.  Evaluation of Himawari-8 AHI geospatial calibration accuracy using SNPP VIIRS SNO data , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[4]  Jean-Pierre Fillard,et al.  Sub-pixel accuracy location estimation from digital signals , 1992 .

[5]  LI Xiao-kun.  FY-4 Imager: Visible Channel Star Sensing , 2007 .

[6]  Feng Lu,et al.  Channel simulation for FY-4 AGRI , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

[7]  C. Loan.  Computational Frameworks for the Fast Fourier Transform , 1992 .

[8]  Laurence B. Milstein,et al.  Chernoff-Type Bounds for the Gaussian Error Function , 2011, IEEE Transactions on Communications.

[9]  郭强 Guo Qiang,et al.  On-Orbit Modification of Pointing Error for Imager in Geostationary Satellite Based on Star Sensing , 2009 .

[10]  Jian Li,et al.  Hardware Implementation of Fast and Robust Star Centroid Extraction With Low Resource Cost , 2015, IEEE Sensors Journal.

[11]  John P. George,et al.  A review of the space based remote sensing for NWP , 2016, SPIE Asia-Pacific Remote Sensing.

[12]  Xiangqian Wu,et al.  Effects of Ice Decontamination on GOES-12 Imager Calibration , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Peter Seitz,et al.  Optical Superresolution Using Solid-State Cameras And Digita; Signal Processing , 1988 .

[14]  Tao Zhang,et al.  A Novel Systematic Error Compensation Algorithm Based on Least Squares Support Vector Regression for Star Sensor Image Centroid Estimation , 2011, Sensors.

[15]  Zhenfei Song,et al.  Systematic centroid error compensation for the simple Gaussian PSF in an electronic star map simulator , 2014 .

[16]  Michael P. Weinreb,et al.  Estimation of long-term throughput degradation of GOES 8 and 9 visible channels by statistical analysis of star measurements , 1998, Optics + Photonics.

[17]  Carl Christian Liebe,et al.  Accuracy performance of star trackers - a tutorial , 2002 .

[18]  Derek York,et al.  Least squares fitting of a straight line with correlated errors , 1968 .

[19]  Aluned A. Kamel.  GOES image navigation and registration system , 1996, Optics & Photonics.

[20]  Tao Zhang,et al.  A New Sub-Pixel Subdivision Location Algorithm for Star Image , 2009, 2009 2nd International Congress on Image and Signal Processing.

[21]  Yang Jun.  Development and Applications of China's Fengyun (FY) Meteorological Satellite , 2008 .