Optimal attitude and position determination by integration of INS, star tracker, and horizon sensor

Chen

et al. 2019

The star sensor is widely used in attitude control systems of spacecraft for attitude measurement. However, under high dynamic conditions, frame loss and smearing of the star image may appear and result in decreased accuracy or even failure of the star centroid extraction and attitude determination. To improve the performance of the star sensor under dynamic conditions, a gyroscope-assisted star image prediction method and an improved Richardson-Lucy (RL) algorithm based on the ensemble back-propagation neural network (EBPNN) are proposed. First, for the frame loss problem of the star sensor, considering the distortion of the star sensor lens, a prediction model of the star spot position is obtained by the angular rates of the gyroscope. Second, to restore the smearing star image, the point spread function (PSF) is calculated by the angular velocity of the gyroscope. Then, we use the EBPNN to predict the number of iterations required by the RL algorithm to complete the star image deblurring. Finally, simulation experiments are performed to verify the effectiveness and real-time of the proposed algorithm.

Section: Prediction Model Of the Star Imagementioning

confidence: 99%

Star Image Prediction and Restoration under Dynamic Conditions

Chen

et al. 2019

“…A star sensor is an optical navigation instrument with high precision, and it has been used in many different applications [1,2,3,4]. One of them is the navigation inside the atmosphere and daytime navigation is one of the most difficult aspects of this kind of application [5].…”

Section: Introductionmentioning

confidence: 99%

Guide Star Selection for the Three-FOV Daytime Star Sensor

Wang

et al. 2019

To realize the application of the star sensor in the all-day carrier platform, a three-field-of-view (three-FOV) star sensor in short-wave infrared (SWIR) band is considered. This new prototype employs new techniques that can improve the detection capability of the star sensor, when the huge size of star identification feature database becomes a big obstacle. Hence, a way to thin the guide star catalog for three-FOV daytime star sensor is studied. Firstly, an introduction of three-FOV star sensor and an example of three-FOV daytime star sensor with narrow FOV are presented. According to this model and the requirement of triangular star identification method, two constraints based on the number and the brightness of the stars in FOV are put forward for guide star selection. Then on the basis of these constraints, the improved spherical spiral method (ISSM) is proposed and the optimal number of reference points of ISSM is discussed. Finally, to demonstrate the performance of the ISSM, guide star catalogs are generated by ISSM, magnitude filter method (MFM), 1st order self-organizing guide star selection method (1st-SOPM) and the spherical spiral method (SSM), respectively. The results show that the guide star catalog generated by ISSM has the smallest size and the number and brightness characteristics of its guide stars are better than the other methods. ISSM is effective for the guide star selection in the three-FOV daytime star sensor.

“…They are the most accurate optical attitude sensors, at present [1]. Due to their high navigation accuracy, strong autonomy, and lack of cumulative error, they are favored in the aerospace industry [2,3]. As the “eyes” of the spacecraft, the accuracy of the star sensor determines the performance of the spacecraft directly.…”

Section: Introductionmentioning

confidence: 99%

A Star Sensor On-Orbit Calibration Method Based on Singular Value Decomposition

Heikkilä

et al. 2019

The navigation accuracy of a star sensor depends on the estimation accuracy of its optical parameters, and so, the parameters should be updated in real time to obtain the best performance. Current on-orbit calibration methods for star sensors mainly rely on the angular distance between stars, and few studies have been devoted to seeking new calibration references. In this paper, an on-orbit calibration method using singular values as the calibration reference is introduced and studied. Firstly, the camera model of the star sensor is presented. Then, on the basis of the invariance of the singular values under coordinate transformation, an on-orbit calibration method based on the singular-value decomposition (SVD) method is proposed. By means of observability analysis, an optimal model of the star combinations for calibration is explored. According to the physical interpretation of the singular-value decomposition of the star vector matrix, the singular-value selection for calibration is discussed. Finally, to demonstrate the performance of the SVD method, simulation calibrations are conducted by both the SVD method and the conventional angular distance-based method. The results show that the accuracy and convergence speed of both methods are similar; however, the computational cost of the SVD method is heavily reduced. Furthermore, a field experiment is conducted to verify the feasibility of the SVD method. Therefore, the SVD method performs well in the calibration of star sensors, and in particular, it is suitable for star sensors with limited computing resources.