Autonomous Recalibration of Star Trackers

被引:18
|
作者
Enright, John [1 ]
Jovanovic, Ilija [1 ]
Vaz, Brendon [1 ]
机构
[1] Ryerson Univ, Dept Aerosp Engn, Toronto, ON M5B 2K3, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Star trackers; calibration; parameter estimation; extended Kalman filter; nonlinear least squares; ON-ORBIT CALIBRATION; ATTITUDE DETERMINATION; CAMERA CALIBRATION; DISTORTION;
D O I
10.1109/JSEN.2018.2857621
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Star trackers must be calibrated prior to flight so that they can make accurate measurements of star positions within the instrument field of view. This calibration is usually performed in atmosphere and after the sensor is launched; it is not uncommon to observe a small shift in some of the calibration parameters. In this paper, we explore several autonomous strategies for on-orbit recalibration of star trackers. We present an improved version of a popular camera model, develop optimizations to identify optimal parameter values, and validate performance using the data collected from on-orbit sensors. When compared with human-mediated batch processing, autonomous methods have comparable reliability, performance, and commissioning time. The sensor datasets used in this paper come from six Sinclair Interplanetary ST-16 star trackers launched between November 2013 and July 2014. Both batch and autonomous approaches to on-orbit calibration yield improvements in measurement availability as well as a 20%-80% reduction in residual geometric error compared to ground calibrations.
引用
收藏
页码:7708 / 7720
页数:13
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