Joint Estimation of Satellite Attitude and Size Based on ISAR Image Interpretation and Parametric Optimization

Wang, Jiadong; Li, Yachao; Du, Lan; Song, Ming; Xing, Mengdao

doi:10.1109/tgrs.2021.3101805

Cited by 14 publications

(3 citation statements)

References 31 publications

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“…Recently, key point extraction network (KPEN) is developed and a novel method for attitude determination via extracted key points is proposed thereafter [12] . Focused on the size and attitude information of satellite key component, pix2pix generative adversarial network is developed in [13] for ISAR image segmentation. A joint estimation method for satellite attitude and size is proposed and the superiority of which is validated on simulated dataset [13] .…”

Section: Introductionmentioning

confidence: 99%

“…Focused on the size and attitude information of satellite key component, pix2pix generative adversarial network is developed in [13] for ISAR image segmentation. A joint estimation method for satellite attitude and size is proposed and the superiority of which is validated on simulated dataset [13] . However, the above-mentioned methods ignore the scattering characteristics of ISAR images, the performances of which need to be further improved.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint estimation of space target attitude and size based on polarimetric ISAR images and modified U-net model

Cui,

Fu,

Chen

2023

Eighth Asia Pacific Conference on Optics Manufacture and Third International Forum of Young Scientists on Advanced Optical Manu

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint estimation of space target attitude and size based on polarimetric ISAR images and modified U-net model

Cui,

Fu,

Chen

2023

Eighth Asia Pacific Conference on Optics Manufacture and Third International Forum of Young Scientists on Advanced Optical Manu

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“…This makes conventional fusion imaging systems unstable in terms of image quality and does not guarantee consistent results from one fusion to the next, thus making them unreliable for practical applications. In addition, conventional fusion imaging systems are dependent on the quality of the image acquisition equipment as they involve the pre-processing and fusion of images, which not only results in unstable image quality, but also increases the operational workload of the system, thus affecting the imaging efficiency [3] . In addition, the conventional fusion imaging system lacks uniform processing of infrared images, resulting in the clarity and resolution of infrared images are not up to standard.…”

Section: Introductionmentioning

confidence: 99%

Design of an ISAR fusion imaging system based on an orthogonal matching tracking algorithm

Jiao,

Liu,

et al. 2023

Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023)

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The current conventional fusion imaging system mainly relies on the fusion of light scattering information to obtain imaging results, which leads to poor fusion imaging results due to the lack of correction and denoising of images. In this regard, the design of an ISAR fusion imaging system based on an orthogonal matching tracking algorithm is proposed. A long-wave infrared detector is used as the main acquisition design for infrared images, and the hardware structure of the system is designed. The non-uniformity of the IR image is corrected by combining the single-point correction algorithm, and the image is filtered and de-noised, and finally the image pixels are fused by the pixel weighting method. In the experiments, the proposed fusion imaging system is verified for its imaging performance. The experimental results show that the proposed fusion imaging system performs image fusion with low imaging ranging errors and has a more satisfactory fusion imaging performance.

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Separated spacecraft attitude algorithm research based on star sensor multi-information fusion

Wang,

Zhang,

Gao

2024

AIP Advances

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Faced with the problem of poor anti-interference ability of star map recognition technology, in order to improve its anti-interference ability and achieve higher attitude measurement accuracy, this article proposes a star map recognition method based on binary search trees. Star sensors and gyroscopes are combined to solve the problem of the poor real-time performance of star sensors, optimizing the Extended Kalman Filtering (EKF) algorithm. This improves attitude output accuracy and formulates corresponding attitude measurement schemes considering the situation where the star sensor is not visible. The results showed that the improved star pattern recognition algorithm had better adaptability and robustness than the rasterization algorithm, with a high recognition success rate of 95.6% when the star sensor field of view was 3°*3°, while the rasterization algorithm cannot recognize small fields of view. The recognition success rate of the algorithm was 98.6% when the standard deviation of magnitude noise was 2.0 pixels, which was 15.4% higher than the rasterization algorithm. Unlike the EKF algorithm, the optimized EKF algorithm had a higher attitude output accuracy, with an average error of about 0.000 211°; compared to before optimization, it has increased by 93.43%. In the attitude measurement scheme, the relative attitude angle measurement error was small, and the maximum attitude measurement error in the rolling angle direction was 1.8 × 10−3°. This paper adopts a method to achieve high-precision satellite attitude measurement with good adaptability, which can be applied in complex space missions.

show abstract

Joint Estimation of Satellite Attitude and Size Based on ISAR Image Interpretation and Parametric Optimization

Cited by 14 publications

References 31 publications

Joint estimation of space target attitude and size based on polarimetric ISAR images and modified U-net model

Joint estimation of space target attitude and size based on polarimetric ISAR images and modified U-net model

Design of an ISAR fusion imaging system based on an orthogonal matching tracking algorithm

Separated spacecraft attitude algorithm research based on star sensor multi-information fusion

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