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一种基于扩展卡尔曼滤波器的星敏感器姿态跟踪算法

An Extended Kalman Filter-Based Attitude Tracking Algorithm for Star Sensors.

作者信息

Li Jian, Wei Xinguo, Zhang Guangjun

机构信息

School of Instrument Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China.

出版信息

Sensors (Basel). 2017 Aug 21;17(8):1921. doi: 10.3390/s17081921.

DOI:10.3390/s17081921
PMID:28825684
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5580079/
Abstract

Efficiency and reliability are key issues when a star sensor operates in tracking mode. In the case of high attitude dynamics, the performance of existing attitude tracking algorithms degenerates rapidly. In this paper an extended Kalman filtering-based attitude tracking algorithm is presented. The star sensor is modeled as a nonlinear stochastic system with the state estimate providing the three degree-of-freedom attitude quaternion and angular velocity. The star positions in the star image are predicted and measured to estimate the optimal attitude. Furthermore, all the cataloged stars observed in the sensor field-of-view according the predicted image motion are accessed using a catalog partition table to speed up the tracking, called star mapping. Software simulation and night-sky experiment are performed to validate the efficiency and reliability of the proposed method.

摘要

当星敏感器在跟踪模式下运行时，效率和可靠性是关键问题。在高姿态动力学情况下，现有姿态跟踪算法的性能会迅速退化。本文提出了一种基于扩展卡尔曼滤波的姿态跟踪算法。将星敏感器建模为一个非线性随机系统，其状态估计提供三自由度姿态四元数和角速度。通过预测和测量星图中的恒星位置来估计最优姿态。此外，根据预测的图像运动，利用星表分区表访问在传感器视场中观测到的所有编目恒星，以加速跟踪，称为星图映射。进行了软件仿真和夜空实验，以验证所提方法的效率和可靠性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/6a7817554817/sensors-17-01921-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/4503fd0cba27/sensors-17-01921-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/6a7817554817/sensors-17-01921-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/0184a3da8ea5/sensors-17-01921-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/2d9e8668eca3/sensors-17-01921-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/39b8d6d61eaa/sensors-17-01921-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/b70332acbc41/sensors-17-01921-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/6277c2f71f14/sensors-17-01921-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/b5d940a61585/sensors-17-01921-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/91ba1bfd004c/sensors-17-01921-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/c8e5aec6b80b/sensors-17-01921-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/4503fd0cba27/sensors-17-01921-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8542/5580079/6a7817554817/sensors-17-01921-g013.jpg

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本文引用的文献

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Star tracking method based on multiexposure imaging for intensified star trackers.基于多曝光成像的增强型星敏感器星跟踪方法。
Appl Opt. 2017 Jul 20;56(21):5961-5971. doi: 10.1364/AO.56.005961.
2
Effective star tracking method based on optical flow analysis for star trackers.基于光流分析的星敏感器有效星跟踪方法
Appl Opt. 2016 Dec 20;55(36):10335-10340. doi: 10.1364/AO.55.010335.
Sensors (Basel). 2021 Mar 23;21(6):2236. doi: 10.3390/s21062236.
4
INS/CNS Deeply Integrated Navigation Method of Near Space Vehicles.临近空间飞行器INS/CNS深度组合导航方法
Sensors (Basel). 2020 Oct 17;20(20):5885. doi: 10.3390/s20205885.
5
Attitude Angle Compensation for a Synchronous Acquisition Method Based on an MEMS Sensor.基于 MEMS 传感器的同步采集方法的姿态角补偿。
Sensors (Basel). 2019 Jan 24;19(3):483. doi: 10.3390/s19030483.
6
Motion Blurred Star Image Restoration Based on MEMS Gyroscope Aid and Blur Kernel Correction.基于 MEMS 陀螺仪辅助和模糊核校正的运动模糊星像恢复。
Sensors (Basel). 2018 Aug 13;18(8):2662. doi: 10.3390/s18082662.
7
Adaptive Square-Root Unscented Particle Filtering Algorithm for Dynamic Navigation.自适应平方根无迹粒子滤波算法在动态导航中的应用
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8
A New Polar Transfer Alignment Algorithm with the Aid of a Star Sensor and Based on an Adaptive Unscented Kalman Filter.一种借助星敏感器并基于自适应无迹卡尔曼滤波器的新型极坐标传递对准算法。
Sensors (Basel). 2017 Oct 23;17(10):2417. doi: 10.3390/s17102417.