Enhancement of RPC Positioning Accuracy Using Affine Transformation with Different Number of Ground Control Points

2017 ◽  
Vol 17 (17) ◽  
pp. 1-12
Author(s):  
Mohamed Tawfeik ◽  
Hassan Elhifnawy ◽  
Essam Hamza ◽  
Ahmed Shawky ◽  
Ayman Ragab
Keyword(s):  
Affine Transformation ◽  
Ground Control ◽  
Control Points ◽  
Positioning Accuracy ◽  
Ground Control Points

Evaluation of 3D Geo-Positioning Based on Bias-Compensated RPCs for Across-Track QuickBird Stereo Imagery

2012 ◽  
Vol 226-228 ◽  
pp. 1958-1964
Author(s):  
Weian Wang ◽  
Shu Ying Xu ◽  
Gang Qiao
Keyword(s):  
Vertical Direction ◽  
Ground Control ◽  
Control Points ◽  
Accuracy Analysis ◽  
Geometric Correction ◽  
Positioning Accuracy ◽  
Ground Control Points ◽  
Order Polynomial ◽  
Stereo Imagery ◽  
Very High

This paper investigates the geo-positioning accuracy of across-track QuickBird stereo imagery in Shanghai, China, where the terrain relief is very low about 3m but with very high buildings up to 380m. The rational function model (RFM) and the bias-compensated RFM with different parameters are employed to do accuracy analysis with different configurations of ground control points (GCPs). The systematic errors in vendor provided RPCs are revealed and discussed. The results of bias-compensated RFM show that different strategies in terms of the number of GCP and different geometric correction methods should be taken into consideration in order for a better and reasonable positioning accuracy in the three directions. The results also show that the best accuracy of 0.6m in horizontal direction and 0.8m in vertical direction can be acquired by the second-order polynomial model when GCPs are more than 8.

scholarly journals THE PERFORMANCE OF A TIGHT INS/GNSS/PHOTOGRAMMETRIC INTEGRATION SCHEME FOR LAND BASED MMS APPLICATIONS IN GNSS DENIED ENVIRONMENTS

2016 ◽  
Vol XLI-B1 ◽  
pp. 551-557 ◽  
Author(s):  
Chien-Hsun Chu ◽  
Kai-Wei Chiang
Keyword(s):  
Satellite System ◽  
Ground Control ◽  
Integration Scheme ◽  
Control Points ◽  
Mobile Mapping ◽  
Positioning Accuracy ◽  
Variable Position ◽  
Ground Control Points ◽  
Position And Orientation

The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process.

scholarly journals The Geometric Calibration and Validation for The ZY3-02 Satellite Optical Image

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 587-593 ◽  
Author(s):  
X. Tang ◽  
X. Zhu
Keyword(s):  
Earth Observation ◽  
Ground Control ◽  
Control Points ◽  
Registration Accuracy ◽  
Positioning Accuracy ◽  
Geometric Calibration ◽  
Ground Control Points ◽  
System Errors ◽  
Better Than ◽  
Multispectral Camera

Chinese ZY3-02 satellite, which is the second of ZY3 series satellites, was launched in May 30th 2016 for complementing the mapping and earth observation. In order to eliminate various system errors of the platform and payload, the on-orbit geometric validation and calibration was carried out. Firstly, we introduced the parameters of the three-line stereo camera and multispectral camera bound on ZY3-02 in this paper. There are four optical cameras on ZY3-02: a 4-band nadir-looking multi-spectral camera with 5.8 m resolution, a 2.1m resolution nadir-looking panchromatic band camera, as well as 2.5m resolution forward- and backward-looking panchromatic band cameras. Compared with ZY3-01, the resolution of the forward- and backward-looking cameras on ZY3-02 were upgraded from 3.5 m to 2.5 m. Then we presented the methods and datasets used for calibration in details. After our calibration, the total positioning accuracy of the three-line camera images is better than 10m without ground control points (GCPs). The plane and height accuracy are improved to 3 and 2 m respectively, with few control points. The band-to-band registration accuracy of the multispectral camera is better than 0.15 pixels.

scholarly journals THE PERFORMANCE OF A TIGHT INS/GNSS/PHOTOGRAMMETRIC INTEGRATION SCHEME FOR LAND BASED MMS APPLICATIONS IN GNSS DENIED ENVIRONMENTS

2016 ◽  
Vol XLI-B1 ◽  
pp. 551-557
Author(s):  
Chien-Hsun Chu ◽  
Kai-Wei Chiang
Keyword(s):  
Satellite System ◽  
Ground Control ◽  
Integration Scheme ◽  
Control Points ◽  
Mobile Mapping ◽  
Positioning Accuracy ◽  
Variable Position ◽  
Ground Control Points ◽  
Position And Orientation

The early development of mobile mapping system (MMS) was restricted to applications that permitted the determination of the elements of exterior orientation from existing ground control. Mobile mapping refers to a means of collecting geospatial data using mapping sensors that are mounted on a mobile platform. Research works concerning mobile mapping dates back to the late 1980s. This process is mainly driven by the need for highway infrastructure mapping and transportation corridor inventories. In the early nineties, advances in satellite and inertial technology made it possible to think about mobile mapping in a different way. Instead of using ground control points as references for orienting the images in space, the trajectory and attitude of the imager platform could now be determined directly. Cameras, along with navigation and positioning sensors are integrated and mounted on a land vehicle for mapping purposes. Objects of interest can be directly measured and mapped from images that have been georeferenced using navigation and positioning sensors. Direct georeferencing (DG) is the determination of time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using the Global Navigation Satellite System (GNSS) and inertial navigation using an Inertial Measuring Unit (IMU). Although either technology used along could in principle determine both position and orientation, they are usually integrated in such a way that the IMU is the main orientation sensor, while the GNSS receiver is the main position sensor. However, GNSS signals are obstructed due to limited number of visible satellites in GNSS denied environments such as urban canyon, foliage, tunnel and indoor that cause the GNSS gap or interfered by reflected signals that cause abnormal measurement residuals thus deteriorates the positioning accuracy in GNSS denied environments. This study aims at developing a novel method that uses ground control points to maintain the positioning accuracy of the MMS in GNSS denied environments. At last, this study analyses the performance of proposed method using about 20 check-points through DG process.

scholarly journals Geometric Self-Calibration of YaoGan-13 Images Using Multiple Overlapping Images

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2367
Author(s):  
Guo Zhang ◽  
Mingjun Deng ◽  
Chenglin Cai ◽  
Ruishan Zhao
Keyword(s):  
Calibration Method ◽  
High Accuracy ◽  
Ground Control ◽  
Reference Image ◽  
Control Points ◽  
Positioning Accuracy ◽  
Self Calibration ◽  
Ground Control Points ◽  
Absolute Positioning ◽  
The Absolute

Geometric calibration is an important means of improving the absolute positioning accuracy of space-borne synthetic aperture radar imagery. The conventional calibration method is based on a calibration field, which is simple and convenient, but requires a great deal of manpower and material resources to obtain ground control points. Although newer cross-calibration methods do not require ground control points, calibration accuracy still depends on a periodically updated reference image. Accordingly, this study proposes a geometric self-calibration method based on the positioning consistency constraint of conjugate image points to provide rapid and accurate calibration of the YaoGan-13 satellite. The proposed method can accurately calibrate geometric parameters without requiring ground control points or high-precision reference images. To verify the absolute positioning accuracy obtained using the proposed self-calibration method, YaoGan-13 Stripmap images of multiple regions were collected and evaluated. The results indicate that high-accuracy absolute positioning can be achieved with a plane accuracy of 3.83 m or better for Stripmap data, without regarding elevation error. Compared to the conventional calibration method using high-accuracy control data, the difference between the two methods is only about 2.53 m, less than the 3-m resolution of the image, verifying the effectiveness of the proposed self-calibration method.

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