A space surveillance satellite for cataloging high-altitude small debris

Du, Jianli; Lei, Xiangxu; Sang, Jizhang

doi:10.1016/j.actaastro.2019.01.003

Cited by 14 publications

(7 citation statements)

References 4 publications

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“…Space targets can be monitored by space-based sensors [1] , the images of which can be used to analyze the essential characteristics of the obtained target. Moment features are a means of image processing.…”

Section: Introductionmentioning

confidence: 99%

Research on feature extraction method of space targets image based on Hu extension moment

fan,

wang,

et al. 2024

Sixth Conference on Frontiers in Optical Imaging and Technology: Imaging Detection and Target Recognition

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Detection, tracking, characterization and identification of space targets orbiting the Earth is one of the main tasks of the space surveillance system. Spatial target image feature extraction can find out some descriptions that reflect the essence of the target from the original image. The moment feature describes the statistical characteristics of grayscale by the moments of each order of image distribution, which can effectively reflect the shape information of the target. A Hu extension moment is proposed, and a feature extraction method for spatial target images is proposed based on this. It solves the problem of information loss when the confidence variance difference is large and the eigenvalue is negative. A linear combinatorial feature calculation method is proposed for spatial target classification, and a linear classifiable quantitative discrimination method is given. The image needs to be preprocessed. Then, the seven eigenvalues based on the extension moment are calculated, and the similarity analysis of the Hu extension moment is carried out. At last, the similarity of the sample target region matching is analyzed, and the target similarity can reach 90%. For image sets with multiple types of targets, according to the numerical distribution calculates the linear combination feature, linear classifiable quantitative discriminant results can be calculated. 48 images of four satellites in the database were selected as test data. Its recognition accuracy rate reaches 95.8%. Calculating the recognition result of the same platform for multi-sample joint recognition, and the probability of recognition attribution after multi-sample union is 100%.

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Section: Introductionmentioning

confidence: 99%

Research on feature extraction method of space targets image based on Hu extension moment

fan,

wang,

et al. 2024

Sixth Conference on Frontiers in Optical Imaging and Technology: Imaging Detection and Target Recognition

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“…The human trajectory of universe discovery largely depends on the development of space vehicles. As the transportation tool in space, space vehicles associate with activities including planetary exploration aiming moon and Mars [1], space debris collection [2], and surveillance of satellites [3]. The G&C system ensures the efficiency of instruction outputs and operation executions in space vehicles [4].…”

Section: Introductionmentioning

confidence: 99%

Demonstration And Analysis of The Guiding Control System for Aerospace Crafts

Chen¹

2023

HSET

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The development of space vehicle guidance and control systems gradually becomes a focus in recent research as a key to space vehicles’ information processing and control in the space environment. In general, among the popular methods in G&C systems, artificial intelligence-based algorithms contain a wide prospect. This study offers descriptions of the current methods in AI-based algorithms, proposed challenges involved in this field, and described the recent achievements in solving these issues. To be specific, the basic descriptions of the controlling systems as well as the various state-of-art machine learning approaches that are suitable for the G&C system are demonstrated and analyzed including ANN, DNN, RL, SVM, DRL, etc. According to the analysis, the challenges as well as the drawbacks of the advanced scenarios are estimated as well as propose the future prospects to improve the performance of landing. Overall, these results shed light on guiding further exploration of aerospace vehicles.

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“…Space Situation Awareness (SSA) [1][2][3][4] is currently a key research project for various spacefaring nations, which can achieve high-precision real-time tracking of noncooperative targets in space by establishing a combined space and sky satellite surveillance system. Since ground-based observation devices depend on meteorological, geographic, and geophysical conditions, the use of space-based observation systems [5] can circumvent these limitations and play an important role in space deployment, surveillance, and early warning [6][7][8]. Compared with traditional large satellites, micro-/ nanosatellites [9] have a shorter development cycle, lower cost, and more flexible system applications, but micro-/ nanosatellites suffer from limited power supply, small size, and insufficient computing power, which lead to great limitations in the observation equipment carried by micro-/ nanosatellites; therefore, it is of great significance to study optical imaging micro-/nanosatellites to achieve highprecision tracking of space target.…”

Section: Introductionmentioning

confidence: 99%

Angle-Only Target Tracking Method for Optical Imaging Micro-/Nanosatellite Based on APSO-SSUKF

Hua

Yang

et al. 2022

Space Sci Technol

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To ensure the safety of the space station and improve the accuracy of the estimated trajectory tracking of noncooperative target, an optical imaging micro-/nanosatellite based on APSO-SSUKF (adaptive particle swarm optimization-spherical simplex unscented Kalman filter) is proposed to track low-orbit target using angle-only measurement. First, the algorithm considers the effect of J2 perturbation, uses the angle-only data as the observation vector, and uses spherical simplex unscented Kalman filter (SSUKF) to reduce the cost of calculation of the UKF in space noncooperative target tracking. Secondly, it is proposed to use the actual and theoretical covariance of the innovation sequence for real-time estimation of measurement noise, designing the adaptive particle swarm optimization (APSO) algorithm for real-time tracking of the process noise in the SSUKF that improves the accuracy of the filter in angle-only tracking. Finally, the tracking simulation of low-orbit satellite is carried out by using optical imaging micro-/nanosatellite, and the result shows that, compared with UKF, SSUKF, and PSO-SSUKF, APSO-SSUKF reduces the root mean square of the error in predicting the position in space target tracking by 45.44%, 35.26%, and 20.94%, and APSO-SSUKF reduces the root mean square of the error in velocity by 45.58%, 33.53%, and 16.33%, respectively; in the angle-tracking target, APSO-SSUKF improves the convergence and estimated accuracy of the algorithm in tracking.

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A space surveillance satellite for cataloging high-altitude small debris

Cited by 14 publications

References 4 publications

Research on feature extraction method of space targets image based on Hu extension moment

Research on feature extraction method of space targets image based on Hu extension moment

Demonstration And Analysis of The Guiding Control System for Aerospace Crafts

Angle-Only Target Tracking Method for Optical Imaging Micro-/Nanosatellite Based on APSO-SSUKF

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