Adaptive celestial positioning for the stationary Mars rover based on a self-calibration model for the star sensor

2021 ◽  
pp. 1-16
Author(s):  
Yinhu Zhan ◽  
Shaojie Chen ◽  
Xu Zhang
Keyword(s):  
Optical Sensors ◽  
Field Tests ◽  
Calibration Model ◽  
Star Sensor ◽  
Control Points ◽  
Accuracy Improvement ◽  
Mars Rover ◽  
Future Studies ◽  
Self Calibration ◽  
Imaging Model

Abstract This paper proposes a method for self-calibrating the star sensor on the Mars rover considering several years of exploration on the surface of Mars. The natural stars in the night sky are considered the control points, and a self-calibration model is deduced in detail according to an imaging model. An adaptive celestial positioning (ACP) algorithm is then introduced, and the calculation procedure is presented in detail to realise self-adjustment based on the self-calibration of the star sensor. Three field tests were conducted on Earth, the results of which show good self-calibration and celestial positioning performances. The positioning results indicate an obvious accuracy improvement using the ACP algorithm compared with that without calibration. Multiple positionings in one night can improve the celestial positioning accuracy to approximately 15 m. For future studies, this self-calibration model will be useful not only for star sensors but also for other optical sensors, such as sun sensors and binocular or stereo-vision cameras.

scholarly journals GEOMETRIC CALIBRATION OF ZIYUAN-3 THREE-LINE CAMERAS COMBINING GROUND CONTROL POINTS AND LINES

2016 ◽  
Vol XLI-B1 ◽  
pp. 163-168
Author(s):  
Jinshan Cao ◽  
Xiuxiao Yuan ◽  
Jianya Gong
Keyword(s):  
Ground Control ◽  
Calibration Model ◽  
Control Points ◽  
Charge Coupled Device ◽  
Geometric Calibration ◽  
Ground Control Points ◽  
The Look ◽  
Ccd Detectors ◽  
True Values ◽  
Better Than

Due to the large biases between the laboratory-calibrated values of the orientation parameters and their in-orbit true values, the initial direct georeferencing accuracy of the Ziyuan-3 (ZY-3) three-line camera (TLC) images can only reach the kilometre level. In this paper, a point-based geometric calibration model of the ZY-3 TLCs is firstly established by using the collinearity constraint, and then a line-based geometric calibration model is established by using the coplanarity constraint. With the help of both the point-based and the line-based models, a feasible in-orbit geometric calibration approach for the ZY-3 TLCs combining ground control points (GCPs) and ground control lines (GCLs) is presented. Experimental results show that like GCPs, GCLs can also provide effective ground control information for the geometric calibration of the ZY-3 TLCs. The calibration accuracy of the look angles of charge-coupled device (CCD) detectors achieved by using the presented approach reached up to about 1.0''. After the geometric calibration, the direct georeferencing accuracy of the ZY-3 TLC images without ground controls was significantly improved from the kilometre level to better than 11 m in planimetry and 9 m in height. A more satisfactory georeferencing accuracy of better than 3.5 m in planimetry and 3.0 m in height was achieved after the block adjustment with four GCPs.

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

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6668
Author(s):  
Linyi Jiang ◽  
Xiaoyan Li ◽  
Liyuan Li ◽  
Lin Yang ◽  
Lan Yang ◽  
...  
Keyword(s):  
Relative Motion ◽  
Calibration Method ◽  
System Structure ◽  
Calibration Model ◽  
Control Points ◽  
Penetration Process ◽  
Geometric Calibration ◽  
Positioning Errors ◽  
Ground Control Points ◽  
Motion Transformation

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.

scholarly journals Strip-Mode Microwave Staring Correlated Imaging with Self-Calibration of Gain–Phase Errors

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1079 ◽  
Author(s):  
Rui Xia ◽  
Yuanyue Guo ◽  
Weidong Chen ◽  
Dongjin Wang
Keyword(s):  
Error Estimation ◽  
Phase Error ◽  
Super Resolution ◽  
Image Splicing ◽  
Initial Value ◽  
Self Calibration ◽  
Phase Errors ◽  
Imaging Model ◽  
Multiple Imaging ◽  
Imaging Performance

Microwave staring correlated imaging (MSCI) can realize super resolution imaging without the limit of relative motion with the target. However, gain–phase errors generally exist in the multi-transmitter array, which results in imaging model mismatch and degrades the imaging performance considerably. In order to solve the problem of MSCI with gain–phase error in a large scene, a method of MSCI with strip-mode self-calibration of gain–phase errors is proposed. The method divides the whole imaging scene into multiple imaging strips, then the strip target scattering coefficient and the gain–phase errors are combined into a multi-parameter optimization problem that can be solved by alternate iteration, and the error estimation results of the previous strip can be carried into the next strip as the initial value. All strips are processed in multiple rounds, and the gain–phase error estimation results of the last strip can be taken as the initial value and substituted into the first strip for the correlated processing of the next round. Finally, the whole imaging in a large scene can be achieved by multi-strip image splicing. Numerical simulations validate its potential advantages to shorten the imaging time dramatically and improve the imaging and gain–phase error estimation performance.

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

2020 ◽  
Vol 12 (7) ◽  
pp. 1055
Author(s):  
Yanli Wang ◽  
Mi Wang ◽  
Ying Zhu
Keyword(s):  
Remote Sensing ◽  
Coordinate System ◽  
Statistical Characteristics ◽  
Optical Remote Sensing ◽  
Star Sensor ◽  
Control Points ◽  
Remote Sensing Images ◽  
Multiple Star ◽  
Ground Control Points ◽  
Combination Modes

Owing to the vibrations and thermal shocks that arise during the launch and orbit penetration process, the on-orbit installation parameters of multiple star sensors are different from the on-ground measured parameters, causing inconsistencies in the attitude determinations from different combination modes and seriously affecting the geometric accuracy of high-resolution optical remote sensing images. This study presents an on-orbit calibration approach for the installation parameters of a multiple star sensors system using ground control points (GCPs). Based on the on-ground installation parameters of the optical axes of conventional star sensors, a fiducial coordinate system is proposed as the calibration coordinate system. The installation parameters of the conventional star sensors are calibrated using the statistical characteristics of angles between axes of the star sensor and three fiducial vectors in the J2000 celestial coordinate system. Based on the GCPs, the relative fiducial parameters are calculated, and the installation parameter of unconventional star sensor is then calibrated with the relative fiducial parameters and statistical characteristics of angles. It can be used for high-resolution optical remote sensing satellite measuring with only two star sensors to unify the fiducial coordinate system. The proposed method is tested using simulated data and on-orbit measurement data. The results demonstrate that the proposed method can calibrate the optical axis of the star sensor without the restriction of the accuracy of horizontal axis. Moreover, the star sensor with a large installation angle error can be calibrated well using the proposed approach. The results of attitude determinations from different star sensor combination modes are consistent, and the geometric accuracy of the remote sensing images is significantly improved.

Self calibration of camera with non-linear imaging model

2007 ◽  
Author(s):  
Wenguang Hou ◽  
Tao Shang ◽  
Mingyue Ding
Keyword(s):  
Self Calibration ◽  
Imaging Model ◽  
Non Linear

Real-Time Detection System of Soil Moisture Based on GPRS

2011 ◽  
Vol 464 ◽  
pp. 175-178
Author(s):  
Rong Biao Zhang ◽  
Jing Jing Guo ◽  
Qi Wang ◽  
Lei Zhang ◽  
Xian Lin Wang
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Detection System ◽  
Field Tests ◽  
Support Vector ◽  
Calibration Model ◽  
Vector Machines ◽  
Moisture Detection ◽  
Software And Hardware ◽  
Seamless Connection

Real-time monitoring of soil moisture is essential for agricultural production. In this paper, an improved system is designed based on GPRS technology for real-time detecting soil moisture, a salinity calibration model is established based on Least Squares Support Vector Machines on MatLAB (LS-SVMlab) for improving detection precision. The transmission of soil moisture information is the key technology of the system, by software and hardware design we have solved the problems of data congestion, off-line, and moving the monitoring terminal at any time, which still restrict the application of GPRS in soil moisture detection. Field tests show that the system can realize seamless connection between the collection nodes and remote host, and acquire soil moisture accurately. Simultaneously, the time of re-networking has been shortened greatly.

scholarly journals IMPROVING THE INTERNAL ACCURACY OF UAV-IMAGE BLOCKS USING LOCAL LOW-ALTITUDE FLIGHTS AND SCALE-BARS

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 183-188
Author(s):  
M. Maboudi ◽  
A. Elbillehy ◽  
Y. Ghassoun ◽  
M. Gerke
Keyword(s):  
Ground Control ◽  
Accurate Estimation ◽  
Small Scale ◽  
Control Points ◽  
Accuracy Improvement ◽  
Object Space ◽  
Ground Control Points ◽  
Low Altitude ◽  
Uav Image ◽  
Small Parts

Abstract. Accurate image-based measurement based on UAV data is attracting attention in various applications. While the external accuracy of the UAV image blocks could be mainly affected by object-space information like number and distribution of ground control points and RTK-GNSS accuracy, its internal accuracy highly depends on camera specifications, flight height, data capturing setup and accuracy of scale estimation. For many small-scale projects accurate local measurements are highly demanded. This necessitates high internal accuracy of images block which could be transferred from model space to object space by accurate estimation of the scale parameter. This research aims at improving the internal accuracy of UAV image blocks using low-altitude flight(s) over small parts of the project area without using any ground control points. Possible further improvement by using calibrated scale-bars which serve as scale-constraints is also investigated. To this end, different scenarios of the flight configuration and distance measurements in the two photogrammetric blocks are also considered and the results are analyzed. Our investigations show 50% accuracy improvement achieved by performing local flights over small parts of the scene, given that RTK information is available. Moreover, adding accurate scale-bars increased the accuracy improvement to 67%. Furthermore, when RTK information is not available, adding local low-altitude flights and scale-bars decrease the error of local distance measurement form 1–3 meters to less than 4 centimeters.

scholarly journals Star-Based Calibration of the Installation Between the Camera and Star Sensor of the Luojia 1-01 Satellite

2019 ◽  
Vol 11 (18) ◽  
pp. 2081 ◽  
Author(s):  
Zhichao Guan ◽  
Yonghua Jiang ◽  
Jingyin Wang ◽  
Guo Zhang
Keyword(s):  
High Frequency ◽  
Road Network ◽  
Reference Data ◽  
Calibration Method ◽  
Star Sensor ◽  
Control Points ◽  
Positioning Accuracy ◽  
Ground Control Points ◽  
Position Data ◽  
Frequency Calibration

Ground control points (GCPs) are generally used to calibrate the installation between the camera and star sensor of a satellite in orbit and improve the geometric positioning accuracy of the satellite. However, the use of GCPs for high-frequency calibration is difficult, and it is particularly difficult to acquire accurate GCPs for the image of a nightlight satellite. In this study, we developed a camera-star sensor installation calibration method that eliminates the need for GCPs. In the proposed method, the camera and star sensor lenses are simultaneously pointed at the star, and the camera-star sensor installation is accurately calibrated by processing the star map obtained by the camera and star sensors. Reference data such as road network and Moon position data were used to verify the proposed method and evaluate its positioning accuracy. The results of the application of the method to the positioning of the Luojia 1-01 satellite indicated an accuracy within 800 m, which is comparable with that of the traditional method.

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