On-Orbit Calibration of Installation Parameter of Multiple Star Sensors System for Optical Remote Sensing Satellite with Ground Control Points

Wang, Yanli; Wang, Mi; Zhu, Ying

doi:10.3390/rs12071055

Cited by 7 publications

(3 citation statements)

References 26 publications

(24 reference statements)

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“…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 ]. However, the attitude update rate (AUR) of the traditional star sensor is usually 4–10 Hz, which is too low to accomplish navigation tasks independently.…”

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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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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“…R EMOTE sensing plays a significant role in multiple fields, such as environmental monitoring, national security, and scientific exploration [1], [2]. High-precision image positioning is an important aspect of remote sensing and has critical requirements for the accuracy of internal parameters and external installation matrix of camera [3], [4]. Generally, the camera is calibrated meticulously in the laboratory before satellite launching.…”

Section: Introductionmentioning

confidence: 99%

On-Orbit High-Accuracy Geometric Calibration for Remote Sensing Camera Based on Star Sources Observation

Chen

Xing

You

et al. 2022

IEEE Trans. Geosci. Remote Sensing

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The on-orbit calibration technology for internal and external parameters of remote sensing camera is the key to guaranteeing the imaging quality and positioning accuracy. Conventional landmark-based methods are not suitable for satellite missions where landmarks do not work nor for the on-orbit autonomous calibration of large remote sensing constellation. Hence, we introduced an on-orbit geometric calibration method based on star sources observation. By adjusting the satellite attitude, the camera and star sensor can simultaneously detect the star sources. Taking the star sources as control points, a high-accuracy "camera-star sensor" joint geometric calibration model integrating the space-time effects and optical imaging is established, which precisely decouples the deviations caused by the relativistic effects, the distortion of internal parameters, and the bias of external parameters. Furthermore, the procedures of the method are designed for on-orbit autonomous calibration. On-orbit experiments were carried out in several satellites, such as Jilin-1 ShiPin07 (JL-1 SP07). The results showed that the accuracy of internal calibration could reach 0.052" and the error of external installation matrix was within ±1.4". Therefore, the method is attractive for actualizing on-orbit autonomous geometric calibration accurately and complements the conventional methods where the availability of landmarks is hard.

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“…Nevertheless, owing to the launch vibration and the variation of spatial thermal environment, the positioning model will inevitably change, which will ultimately bring about the reduction of the geometric accuracy [ 8 , 9 ]. Therefore, on-orbit geometric calibration with the references including the ground control points (GCPs), coastlines and stars [ 10 , 11 , 12 , 13 , 14 ] is an essential prerequisite for ensuring the high-precision satellite imagery [ 15 , 16 , 17 , 18 ]. However, for geostationary RSCs, subjected to the cloud coverage and the accuracy of corresponding extraction algorithms, it is not easy to ensure the availability of a great number of accurate GCPs through earth observation, and, additionally, the star-based calibration method is usually limited by the number of the observed stars.…”

Section: Introductionmentioning

confidence: 99%

On-Orbit Geometric Calibration from the Relative Motion of Stars for Geostationary Cameras

Jiang

et al. 2021

Sensors

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Affected by the vibrations and thermal shocks during launch and the orbit penetration process, the geometric positioning model of the remote sensing cameras measured on the ground will generate a displacement, affecting the geometric accuracy of imagery and requiring recalibration. Conventional methods adopt the ground control points (GCPs) or stars as references for on-orbit geometric calibration. However, inescapable cloud coverage and discontented extraction algorithms make it extremely difficult to collect sufficient high-precision GCPs for modifying the misalignment of the camera, especially for geostationary satellites. Additionally, the number of the observed stars is very likely to be inadequate for calibrating the relative installations of the camera. In terms of the problems above, we propose a novel on-orbit geometric calibration method using the relative motion of stars for geostationary cameras. First, a geometric calibration model is constructed based on the optical system structure. Then, we analyze the relative motion transformation of the observed stars. The stellar trajectory and the auxiliary ephemeris are used to obtain the corresponding object vector for correcting the associated calibration parameters iteratively. Experimental results evaluated on the data of a geostationary experiment satellite demonstrate that the positioning errors corrected by this proposed method can be within ±2.35 pixels. This approach is able to effectively calibrate the camera and improve the positioning accuracy, which avoids the influence of cloud cover and overcomes the great dependence on the number of the observed stars.

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On-Orbit Calibration of Installation Parameter of Multiple Star Sensors System for Optical Remote Sensing Satellite with Ground Control Points

Cited by 7 publications

References 26 publications

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

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

On-Orbit High-Accuracy Geometric Calibration for Remote Sensing Camera Based on Star Sources Observation

On-Orbit Geometric Calibration from the Relative Motion of Stars for Geostationary Cameras

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