Detection and Classification of Astronomical Targets with Deep Neural Networks in Wide Field Small Aperture Telescopes
Taiyuan University of Technology(太原理工大学)
Peng Jia, Qiang Liu, Yongyang Sun
备注:
Accepted by Astronomical Journal. The complete code can be downloaded from https://doi.org/10.12149/101016. This code can be directly used to process images obtained by WFSATs. Images obtained by ordinary sky survey telescopes can also be processed with this code, however more annotated images are required to train the neural network
Wide field small aperture telescopes are widely used for optical transient observations. Detection and classification of astronomical targets in observed images are the most important and basic step. In this paper, we propose an astronomical targets detection and classification framework based on deep neural networks. Our framework adopts the concept of the Faster R-CNN and uses a modified Resnet-50 as backbone network and a Feature Pyramid Network to extract features from images of different astronomical targets. To increase the generalization ability of our framework, we use both simulated and real observation images to train the neural network. After training, the neural network could detect and classify astronomical targets automatically. We test the performance of our framework with simulated data and find that our framework has almost the same detection ability as that of the traditional method for bright and isolated sources and our framework has 2 times better detection ability for dim targets, albeit all celestial objects detected by the traditional method can be classified correctly. We also use our framework to process real observation data and find that our framework can improve 25 % detection ability than that of the traditional method when the threshold of our framework is 0.6. Rapid discovery of transient targets is quite important and we further propose to install our framework in embedded devices such as the Nvidia Jetson Xavier to achieve real-time astronomical targets detection and classification abilities.
Radio interferometry is the current method of choice for deep space astronomy, but in the past few decades optical techniques have become increasingly common. This research seeks to characterize the performance of aperture masking interferometry in the near-infrared at small scales. A mask containing six pairs of apertures at varying diameters and separations was constructed for use with a 24-inch telescope at the MIT Wallace Astrophysical Observatory. Test images of Spica and Jupiter were captured for 28 different telescope configurations, varying aperture separation, aperture diameter, colle…
Taiyuan University of Technology(太原理工大学);Durham University(杜伦大学)
Wide field small aperture telescopes (WFSATs) are commonly used for fast sky survey. Telescope arrays composed by several WFSATs are capable to scan sky several times per night. Huge amount of data would be obtained by them and these data need to be processed immediately. In this paper, we propose ARGUS (Astronomical taRGets detection framework for Unified telescopes) for real-time transit detection. The ARGUS uses a deep learning based astronomical detection algorithm implemented in embedded devices in each WFSATs to detect astronomical targets. The position and probability of a detection bei…
Speckle Imaging based on triple correlation is a very efficient image reconstruction technique which is used to retrieve Fourier phase information of the object in presence of atmospheric turbulence. We have developed both Direct Bispectrum and Radon transform based Tomographic speckle masking algorithms to retrieve atmospherically distorted astronomical images. The latter is a much computationally efficient technique because it works with one dimensional image projections. Tomographic speckle imaging provides good image recovery like direct bispectrum but with a large improvement in computati…
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Segmented telescopes are a possibility to enable large-aperture space telescopes for the direct imaging and spectroscopy of habitable worlds. However, the complexity of their aperture geometry, due to the central obstruction, support structures and segment gaps, makes high-contrast imaging challenging. The High-contrast Imager for Complex Aperture Telescopes (HiCAT) testbed was designed to study and develop solutions for such telescope pupils using wavefront control and coronagraphic starlight suppression. The testbed design has the flexibility to enable studies with increasing complexity for …
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Two high performance coronagraphic approaches compatible with segmented and obstructed telescope pupils are described. Both concepts use entrance pupil amplitude apodization and a combined phase and amplitude focal plane mask to achieve full coronagraphic extinction of an on-axis point source. While the first concept, named Apodized Pupil Complex Mask Lyot Coronagraph (APCMLC), relies on a transmission mask to perform the pupil apodization, the second concept, named Phase-Induced Amplitude Apodization complex mask coronagraph (PIAACMC), uses beam remapping for lossless apodization. Both concep…
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Point spread function modelling for astronomical telescopes: a review focused on weak gravitational lensing studies
CEA(法国原子能和替代能源委员会);CNRS(法国国家科学研究中心);AIM(天体物理与宇宙学研究所);University College London (UCL)(伦敦大学学院);Mullard Space Science Laboratory(穆拉德空间科学实验室);Institute of Astrophysics(天体物理研究所)
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Institute of Space Systems, Universität Stuttgart(斯图加特大学空间系统研究所);The German SOFIA Institute (Deutsches SOFIA Institut, DSI)(德国SOFIA研究所);SOFIA Science Center, NASA Ames Research Center(NASA艾姆斯研究中心SOFIA科学中心)
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