Research on angles-only/SINS/CNS relative position and attitude determination algorithm for a tumbling spacecraft

2016 ◽  
Vol 231 (2) ◽  
pp. 218-228 ◽  
Author(s):  
Lijun Zhang ◽  
Shan Qian ◽  
Shifeng Zhang ◽  
Hong Cai
Keyword(s):  
Relative Position ◽  
Navigation System ◽  
Attitude Determination ◽  
A Priori ◽  
Celestial Navigation ◽  
Inertia Parameter ◽  
Rate Information ◽  
Final Approach ◽  
Tumbling Target ◽  
Target Spacecraft

In this paper, the relative navigation technique of final approach phase for a tumbling target spacecraft is studied and exploited. It is assumed that the tumbling target is in failure or out of control and there is no good a priori rotation rate information. The Euler’s rotational dynamics is used to propagate the target angular velocity, and the unknown inertia parameter circumstance is also considered. The chaser spacecraft is equipped with three strapdown gyros and accelerometers and a star sensor that determine the absolute motion parameters, and an optical camera that measures relative azimuth and elevation angles to the target spacecraft. On the basis of the rotational and translational motions of both spacecrafts, an angles-only/ strapdown inertial navigation system/celestial navigation system navigation filter is designed. Simulation results indicate that the proposed algorithm can accurately estimate the relative position, velocity, and attitude between two spacecrafts and compensate the biases of the gyros and accelerometers.

scholarly journals SINS/Landmark Integrated Navigation Based on Landmark Attitude Determination

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2917
Author(s):  
Shuqing Xu ◽  
Haiyin Zhou ◽  
Jiongqi Wang ◽  
Zhangming He ◽  
Dayi Wang
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Attitude Determination ◽  
Feature Matching ◽  
Integrated Navigation ◽  
Basic Scheme ◽  
Integrated Navigation System ◽  
Celestial Navigation ◽  
Landmark Navigation ◽  
Navigation Method

Based on the situation that the traditional SINS (strapdown inertial navigation system)/CNS (celestial navigation system) integrated navigation system fails to realize all-day and all-weather navigation, this paper proposes a SINS/Landmark integrated navigation method based on landmark attitude determination to solve this problem. This integrated navigation system takes SINS as the basic scheme and uses landmark navigation to correct the error of SINS. The way of the attitude determination is to use the landmark information photographed by the landmark camera to complete feature matching. The principle of the landmark navigation and the process of attitude determination are discussed, and the feasibility of landmark attitude determination is analyzed, including the orthogonality of the attitude transform matrix, as well as the influences of the factors such as quantity and geometric position of landmarks. On this basis, the paper constructs the equations of the SINS/Landmark integrated navigation system, testifies the effectiveness of landmark attitude determination on the integrated navigation by Kalman filter, and improves the navigation precision of the system.

Integration of Star and Inertial Sensors for Spacecraft Attitude Determination

2017 ◽  
Vol 70 (6) ◽  
pp. 1335-1348 ◽  
Author(s):  
Kedong Wang ◽  
Tongqian Zhu ◽  
Yujie Qin ◽  
Chao Zhang ◽  
Yong Li
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Attitude Determination ◽  
Inertial Sensors ◽  
Image Plane ◽  
Tracking Mode ◽  
Celestial Navigation ◽  
Acquisition Mode ◽  
Star Pattern Recognition ◽  
Cascaded Filter

A new integration of the acquisition and tracking modes is proposed for the integration of a Celestial Navigation System (CNS) and a Strapdown Inertial Navigation System (SINS). After the integration converges in the acquisition mode, it switches to the tracking mode. In the tracking mode, star pattern recognition is unnecessary and the integration is implemented in a cascaded filter scheme. A pre-filter is designed for each identified star and the output of the pre-filter is fused with the attitude of the SINS in the cascaded navigation filter. Both the pre-filter and the navigation filter are designed in detail. The measurements of the pre-filter are the positions on the image plane of one identified star. Both the starlight direction and its error are estimated in the pre-filter. The estimated starlight directions of all identified stars are the measurements of the navigation filter. The simulation results show that both the reliability and accuracy of the integration are improved and the integration is effective when only one star is identified in a period.

Multi-spacecraft collaborative attitude determination of space tumbling target with experimental verification

2021 ◽  
Vol 185 ◽  
pp. 1-13
Author(s):  
Di Zhao ◽  
Chong Sun ◽  
Zhanxia Zhu ◽  
Wenya Wan ◽  
Zixuan Zheng ◽  
...  
Keyword(s):  
Experimental Verification ◽  
Attitude Determination ◽  
Tumbling Target

Ephemeris Error Correction in Celestial Navigation System Considering Earth’s Precession-Nutation

Optik ◽  
2020 ◽  
pp. 166152
Author(s):  
Bin Gou ◽  
Ke-yu Qi ◽  
Yong-mei Cheng ◽  
Yuan-yuan Xu ◽  
Zhen Sun
Keyword(s):  
Error Correction ◽  
Navigation System ◽  
Celestial Navigation

Multivariate Constrained GNSS Real-time Full Attitude Determination Based on Attitude Domain Search

2018 ◽  
Vol 72 (2) ◽  
pp. 483-502
Author(s):  
Hongtao Wu ◽  
Xiubin Zhao ◽  
Chunlei Pang ◽  
Liang Zhang ◽  
Bo Feng
Keyword(s):  
Objective Function ◽  
Success Rate ◽  
High Efficiency ◽  
Attitude Determination ◽  
A Priori ◽  
Three Dimensional ◽  
Satellite System ◽  
New Method ◽  
Lambda Method ◽  
Attitude Angle

A priori attitude information can improve the success rate and reliability of Global Navigation Satellite System (GNSS) multi-antennae attitude determination. However, a priori attitude information is nonlinear, and integrating a priori information into the objective function rigorously will increase the complexity of an ambiguity domain search, such as the Multivariate Constrained-Least-squares Ambiguity Decorrelation Adjustment (MC-LAMBDA) method. In this paper, a new method based on attitude domain search is presented to make use of the a priori attitude angle information with high efficiency. First, the a priori information of pitch and roll is integrated into the search process to derive the analytic search step for attitude angle, and the integer candidates are determined by traversal search in the three-dimensional attitude domain. Then, the objective function is parameterised with Euler angles, and a non-iterative approximate method is utilised to simplify the iterative computation in calculating objective function values. Experimental results reveal that compared to the MC-LAMBDA method, our new method has the same success rate and reliability, but higher efficiency in making use of a priori attitude information.

Design of a low-cost attitude determination GPS/INS integrated navigation system

GPS Solutions ◽  
2005 ◽  
Vol 9 (4) ◽  
pp. 294-311 ◽  
Author(s):  
Dong-Hwan Hwang ◽  
Sang Heon Oh ◽  
Sang Jeong Lee ◽  
Chansik Park ◽  
Chris Rizos
Keyword(s):  
Navigation System ◽  
Attitude Determination ◽  
Low Cost ◽  
Integrated Navigation ◽  
Integrated Navigation System

Structured condition number and its application in celestial navigation system with variable observability degree

2018 ◽  
Vol 12 (2) ◽  
pp. 182-192 ◽  
Author(s):  
Jin Liu ◽  
Xiao-Lin Ning ◽  
Xin Ma ◽  
Ming-Zhen Gui ◽  
Jian-Cheng Fang ◽  
...  
Keyword(s):  
Condition Number ◽  
Navigation System ◽  
Celestial Navigation

scholarly journals Efficient Star Identification Using a Neural Network

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3684
Author(s):  
David Rijlaarsdam ◽  
Hamza Yous ◽  
Jonathan Byrne ◽  
Davide Oddenino ◽  
Gianluca Furano ◽  
...  
Keyword(s):  
Neural Network ◽  
Attitude Determination ◽  
Lightweight Design ◽  
A Priori ◽  
Search Time ◽  
Identification Algorithm ◽  
Star Sensor ◽  
Feature Extraction Method ◽  
Star Identification ◽  
Space Star

The required precision for attitude determination in spacecraft is increasing, providing a need for more accurate attitude determination sensors. The star sensor or star tracker provides unmatched arc-second precision and with the rise of micro satellites these sensors are becoming smaller, faster and more efficient. The most critical component in the star sensor system is the lost-in-space star identification algorithm which identifies stars in a scene without a priori attitude information. In this paper, we present an efficient lost-in-space star identification algorithm using a neural network and a robust and novel feature extraction method. Since a neural network implicitly stores the patterns associated with a guide star, a database lookup is eliminated from the matching process. The search time is therefore not influenced by the number of patterns stored in the network, making it constant (O(1)). This search time is unrivalled by other star identification algorithms. The presented algorithm provides excellent performance in a simple and lightweight design, making neural networks the preferred choice for star identification algorithms.

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