The log-polar transform （LPT） is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift...The log-polar transform （LPT） is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift of the feature vector and to reduce the time consumed in the star identification algorithm using LPT. In the proposed algorithm, the star pattern of the same navigation star remains unchanged when the stellar image is rotated, which makes it able to reduce the star identification time. The logarithmic values of the plane distances between the navigation and its neighbor stars are adopted to structure the feature vector of the navigation star, which enhances the robustness of star identification. In addition, some efforts are made to make it able to find the identification result with fewer comparisons, instead of searching the whole feature database. The simulation results demonstrate that the proposed algorithm can effectively acceldrate the star identification. Moreover, the recognition rate and robustness by the proposed algorithm are better than those by the LPT algorithm and the modified grid algorithm.展开更多
The star identification algorithm usually identifies stars by angular distance matching.However,under high dynamic conditions,the rolling shutter effect distorts the angular distances between the measured and true sta...The star identification algorithm usually identifies stars by angular distance matching.However,under high dynamic conditions,the rolling shutter effect distorts the angular distances between the measured and true star positions,leading to plethoric false matches and requiring complex and time-consuming verification for star identification.Low identification rate hinders the application of low-noise and cost-effective rolling shutter image sensors.In this work,we first study a rolling shutter distortion model of angular distances between stars,and then propose a novel three-stage star identification algorithm to identify distorted star images captured by the rolling shutter star sensor.The first stage uses a modified grid algorithm with adaptive error tolerance and an expanded pattern database to efficiently eliminate spurious matches.The second stage performs angular velocity estimation based on Hough transform to verify the matches that follow the same distortion pattern.The third stage applies a rolling shutter error correction method for further verification.Both the simulation and night sky image test demonstrate the effectiveness and efficiency of our algorithm under high dynamic conditions.The accuracy of angular velocity estimation method by Hough transform is evaluated and the root mean square error is below 0.5(°)/s.Our algorithm achieves a 95.7% identification rate at an angular velocity of 10(°)/s,which is much higher than traditional algorithms.展开更多
An artificial intelligence enhanced star identification algorithm is proposed for star trackers in lost-inspace mode.A convolutional neural network model based on Vgg16 is used in the artificial intelligence algorithm...An artificial intelligence enhanced star identification algorithm is proposed for star trackers in lost-inspace mode.A convolutional neural network model based on Vgg16 is used in the artificial intelligence algorithm to classify star images.The training dataset is constructed to achieve the networks’optimal performance.Simulation results show that the proposed algorithm is highly robust to many kinds of noise,including position noise,magnitude noise,false stars,and the tracker’s angular velocity.With a deep convolutional neural network,the identification accuracy is maintained at 96%despite noise and interruptions,which is a significant improvement to traditional pyramid and grid algorithms.展开更多
We present near-infrared spectroscopic and photometric observations of nova V5584 Sgr taken during the first 12 d following its discovery on Oct. 26.439 UT2009. The evolution of the spectra is shown from the initial P...We present near-infrared spectroscopic and photometric observations of nova V5584 Sgr taken during the first 12 d following its discovery on Oct. 26.439 UT2009. The evolution of the spectra is shown from the initial P Cygni phase to an emission line phase. The prominent carbon lines seen in the JHK spectra closely match those observed in an Fe II class nova outburst. The spectra show first-overtone CO bands in emission between 2.29-2.40 μm. By examining WISE and other publicly available data, we show that the nova underwent a pronounced dust formation phase between February- April 2010.展开更多
A star identification algorithm was developed for a charge-coupled device （CCD） or complementary metal-oxide-semiconductor （CMOS） autonomous star tracker to acquire 3-axis attitude information for a lost-in-space ...A star identification algorithm was developed for a charge-coupled device （CCD） or complementary metal-oxide-semiconductor （CMOS） autonomous star tracker to acquire 3-axis attitude information for a lost-in-space spacecraft. The algorithm took advantage of an efficient on-board database and an original “4- star matching” pattern recognition strategy to achieve fast and reliable star identification. The on-board database was composed of a brightness independent guide star catalog （mission catalog） and a K-vector star pair catalog. The star pattern recognition method involved direct location of star pair candidates and a sim- ple array matching procedure. Tests of the algorithm with a CMOS active pixel sensor （APS） star tracker result in a 99.9% success rate for star identification for lost-in-space 3-axis attitude acquisition when the angular measurement accuracy of the star tracker is at least 0.01°. The brightness independent algorithm requires relatively higher measurement accuracy of the star apparent positions that can be easily achieved by CCD or CMOS sensors along with subpixel centroiding techniques.展开更多
We propose an efficient, specific method for estimating camera parameters from a single starry night image. Such an image consists of a collection of disks representing stars, so traditional estimation methods for com...We propose an efficient, specific method for estimating camera parameters from a single starry night image. Such an image consists of a collection of disks representing stars, so traditional estimation methods for common pictures do not work. Our method uses a database, a star catalog, that stores the positions of stars on the celestial sphere. Our method computes magnitudes(i.e., brightnesses) of stars in the input image and uses them to find the corresponding stars in the star catalog. Camera parameters can then be estimated by a simple geometric calculation. Our method is over ten times faster and more accurate than a previous method.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61172138 and 61401340)the Open Research Fund of the Academy of Satellite Application,China(Grant No.2014 CXJJ-DH 12)+3 种基金the Fundamental Research Funds for the Central Universities,China(Grant Nos.JB141303 and201413B)the Natural Science Basic Research Plan in Shaanxi Province,China(Grant No.2013JQ8040)the Research Fund for the Doctoral Program of Higher Education of China(Grant No.20130203120004)the Xi’an Science and Technology Plan,China(Grant.No CXY1350(4))
文摘The log-polar transform （LPT） is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift of the feature vector and to reduce the time consumed in the star identification algorithm using LPT. In the proposed algorithm, the star pattern of the same navigation star remains unchanged when the stellar image is rotated, which makes it able to reduce the star identification time. The logarithmic values of the plane distances between the navigation and its neighbor stars are adopted to structure the feature vector of the navigation star, which enhances the robustness of star identification. In addition, some efforts are made to make it able to find the identification result with fewer comparisons, instead of searching the whole feature database. The simulation results demonstrate that the proposed algorithm can effectively acceldrate the star identification. Moreover, the recognition rate and robustness by the proposed algorithm are better than those by the LPT algorithm and the modified grid algorithm.
基金supported by the National Key Research and Development Program of China(No.2019YFA0706002).
文摘The star identification algorithm usually identifies stars by angular distance matching.However,under high dynamic conditions,the rolling shutter effect distorts the angular distances between the measured and true star positions,leading to plethoric false matches and requiring complex and time-consuming verification for star identification.Low identification rate hinders the application of low-noise and cost-effective rolling shutter image sensors.In this work,we first study a rolling shutter distortion model of angular distances between stars,and then propose a novel three-stage star identification algorithm to identify distorted star images captured by the rolling shutter star sensor.The first stage uses a modified grid algorithm with adaptive error tolerance and an expanded pattern database to efficiently eliminate spurious matches.The second stage performs angular velocity estimation based on Hough transform to verify the matches that follow the same distortion pattern.The third stage applies a rolling shutter error correction method for further verification.Both the simulation and night sky image test demonstrate the effectiveness and efficiency of our algorithm under high dynamic conditions.The accuracy of angular velocity estimation method by Hough transform is evaluated and the root mean square error is below 0.5(°)/s.Our algorithm achieves a 95.7% identification rate at an angular velocity of 10(°)/s,which is much higher than traditional algorithms.
基金the National Natural Science Foundation of China(No.6152403)。
文摘An artificial intelligence enhanced star identification algorithm is proposed for star trackers in lost-inspace mode.A convolutional neural network model based on Vgg16 is used in the artificial intelligence algorithm to classify star images.The training dataset is constructed to achieve the networks’optimal performance.Simulation results show that the proposed algorithm is highly robust to many kinds of noise,including position noise,magnitude noise,false stars,and the tracker’s angular velocity.With a deep convolutional neural network,the identification accuracy is maintained at 96%despite noise and interruptions,which is a significant improvement to traditional pyramid and grid algorithms.
基金funded by the Department of Space, Government of India
文摘We present near-infrared spectroscopic and photometric observations of nova V5584 Sgr taken during the first 12 d following its discovery on Oct. 26.439 UT2009. The evolution of the spectra is shown from the initial P Cygni phase to an emission line phase. The prominent carbon lines seen in the JHK spectra closely match those observed in an Fe II class nova outburst. The spectra show first-overtone CO bands in emission between 2.29-2.40 μm. By examining WISE and other publicly available data, we show that the nova underwent a pronounced dust formation phase between February- April 2010.
基金Supported by the National Key Basic Research and Development (973) Program of China (No. G2000077606 )
文摘A star identification algorithm was developed for a charge-coupled device （CCD） or complementary metal-oxide-semiconductor （CMOS） autonomous star tracker to acquire 3-axis attitude information for a lost-in-space spacecraft. The algorithm took advantage of an efficient on-board database and an original “4- star matching” pattern recognition strategy to achieve fast and reliable star identification. The on-board database was composed of a brightness independent guide star catalog （mission catalog） and a K-vector star pair catalog. The star pattern recognition method involved direct location of star pair candidates and a sim- ple array matching procedure. Tests of the algorithm with a CMOS active pixel sensor （APS） star tracker result in a 99.9% success rate for star identification for lost-in-space 3-axis attitude acquisition when the angular measurement accuracy of the star tracker is at least 0.01°. The brightness independent algorithm requires relatively higher measurement accuracy of the star apparent positions that can be easily achieved by CCD or CMOS sensors along with subpixel centroiding techniques.
文摘We propose an efficient, specific method for estimating camera parameters from a single starry night image. Such an image consists of a collection of disks representing stars, so traditional estimation methods for common pictures do not work. Our method uses a database, a star catalog, that stores the positions of stars on the celestial sphere. Our method computes magnitudes(i.e., brightnesses) of stars in the input image and uses them to find the corresponding stars in the star catalog. Camera parameters can then be estimated by a simple geometric calculation. Our method is over ten times faster and more accurate than a previous method.
