Star Identification Based on Multilayer Voting Algorithm for Star Sensors

Wei, Xin; Wen, Desheng; Wang, Hu

doi:10.3390/s21093084

Cited by 12 publications

(5 citation statements)

References 30 publications

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“…We use the discretization mathematical idea to set the temperature control conditions as the small grid temperature matrix, as shown in Figure 6. We obtain the set temperature gradient matrix (∆T 0-row ) by decomposing the set temperature conditions and calculate the actual temperature gradient matrix (∆T row ) from the actual temperature matrix, for example, the row direction temperature gradient matrix as shown in Equation (10).…”

Section: Conversion Algorithm For Thermal Conditionsmentioning

confidence: 99%

“…However, the evaluation of thermal deformation currently relies pri ulation analysis and lacks direct testing of object deformation. Several un Similarly, in the calibration of star sensors, the thermal deformation frame of the dome-type multi-star simulator (Figure 3) significantly impac simulation accuracy of the simulator [9][10][11][12]. By identifying the thermal d rection of the support frame, timely correction of the thermal deformation prove the simulation accuracy of the star simulator.…”

Section: Introductionmentioning

confidence: 99%

“…However, the evaluation of thermal deformation currently relies prim ulation analysis and lacks direct testing of object deformation. Several unr Similarly, in the calibration of star sensors, the thermal deformation of the supp frame of the dome-type multi-star simulator (Figure 3) significantly impacts the star m simulation accuracy of the simulator [9][10][11][12]. By identifying the thermal deformation rection of the support frame, timely correction of the thermal deformation error can prove the simulation accuracy of the star simulator.…”

Section: Introductionmentioning

confidence: 99%

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Research on a Super-Sub-Arc Bivariate Relative Angle Thermal Deformation Testing Method without Pitch Angle Limitation

Liu,

Xue,

Wang

et al. 2023

Applied Sciences

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In light of the current situation where no testing equipment is available for measuring thermal deformation of objects, this paper proposes a novel method for accurate and precise measurement. The method overcomes the limitations of previous approaches that relied on pitch angle. By utilizing the principle of biplane multiple reflections, a bivariate laser spot displacement analysis algorithm is devised to attain highly precise measurements of bivariate angles. Additionally, a temperature gradient comparison algorithm is introduced to calculate the indicator test results under specific temperature conditions. To validate the effectiveness and reliability of this method, a testing system is constructed and utilized. The results demonstrate that the thermal deformation angle change test achieves an impressive accuracy of 0.015″ and a rate of thermal deformation angle change of 0.3247″/°C. These values are in close agreement with the previously simulated analysis result of 0.359″/°C, with only a relative error of 9.55%. Therefore, the test results confirm the efficacy and reliability of this testing method along with the feasibility of the algorithm processing.

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Section: Conversion Algorithm For Thermal Conditionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on a Super-Sub-Arc Bivariate Relative Angle Thermal Deformation Testing Method without Pitch Angle Limitation

Liu,

Xue,

Wang

et al. 2023

Applied Sciences

Self Cite

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show abstract

“…The star sensor is currently known as the most accurate attitude measurement instrument, and it also has the characteristics of no drift and autonomy [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ]. Therefore, the star sensor has been widely used in the field of aerospace navigation [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

A High-Accuracy Star Centroid Extraction Method Based on Kalman Filter for Multi-Exposure Imaging Star Sensors

Yu,

Qu,

Zhang

2023

Sensors

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A multi-exposure imaging approach proposed in earlier studies is used to increase star sensors’ attitude update rate by N times. Unfortunately, serious noises are also introduced in the star image due to multiple exposures. Therefore, a star centroid extraction method based on Kalman Filter is proposed in this paper. Firstly, star point prediction windows are generated based on centroids’ kinematic model. Secondly, the classic centroid method is used to calculate the coarse centroids of the star points within the prediction windows. Lastly, the coarse centroids are, respectively, processed by each Kalman Filter to filter image noises, and thus fine centroids are obtained. Simulations are conducted to verify the Kalman-Filter-based estimation model. Under noises with zero mean and ±0.4, ±1.0, and ±2.5 pixel maximum deviations, the coordinate errors after filtering are reduced to about 37.5%, 26.3%, and 20.7% of the original ones, respectively. In addition, experiments are conducted to verify the star point prediction windows. Among 100 star images, the average proportion of the number of effective star point objects obtained by the star point prediction windows in the total object number of each star image is calculated as only 0.95%. Both the simulated and experimental results demonstrate the feasibility and effectiveness of the proposed method.

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“…1. We aimed to solve the problem of star identification over the entire sky using an autonomous recognition algorithm based on a compound calibration star grid pattern (Liu et al 2021). The main algorithm included initial matching and verification.…”

mentioning

confidence: 99%

Research on Star Sensor-based Space Debris Detection and Positioning Technology

Liu

2023

PASP

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As an important part of space situational awareness, space-based surveillance of space debris is of great significance for understanding and protecting space resources. With the increasing number of spacecraft operating in the Earth's orbit, both the environment and the space security situation have gradually deteriorated. The accurate detection of small, dim targets in space is the technical basis of space-based debris monitoring; however, several difficulties exist in this field. Since space targets reflect low light energy, the number of pixels occupied by the target is small, and they do not reveal shape or texture characteristics. Space debris is therefore easily confused with background stars, leading to many false alarm targets, and making source detection, recognition, and tracking challenging. Accurate source positions for small and dim space targets are therefore important motivators in our project. However, the positioning accuracy of existing space-based monitoring platforms is limited by the position of the observation platform and the observable time period, due to the high-speed movements of the satellite platform and the observation target. The observation efficiency of existing space-based monitoring platforms is also low, which has certain limitations in practical applications. The high-precision measurement of target positions is thus inhibited when using existing space-based monitoring platforms. The aim of this research is to use an autonomous recognition algorithm based on a compound calibration star grid pattern for star identification. This study utilized a national advanced research project from the National High Technology Research and Development Program and used a star sensor for space debris monitoring, allowing dim and small space debris to be distinguished from stars. This research proposes a target detection technology path based on local sky reference star image comparison to detect weak and small targets in the background of star images. This technology enables the rapid, effective recognition and high-precision positioning of small, dim space targets.

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Star Identification Based on Multilayer Voting Algorithm for Star Sensors

Cited by 12 publications

References 30 publications

Research on a Super-Sub-Arc Bivariate Relative Angle Thermal Deformation Testing Method without Pitch Angle Limitation

Research on a Super-Sub-Arc Bivariate Relative Angle Thermal Deformation Testing Method without Pitch Angle Limitation

A High-Accuracy Star Centroid Extraction Method Based on Kalman Filter for Multi-Exposure Imaging Star Sensors

Research on Star Sensor-based Space Debris Detection and Positioning Technology

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