Direct Georeferencing Accuracy Research Articles

BUNDLE BLOCK ADJUSTMENT WITH SELF-CALIBRATION OF LONG ORBIT CBERS-02B IMAGERY

Abstract. CBERS-02B was the first high resolution earth observation satellite in China, which adopted linear array push-broom sensor. The nadir ground resolution of the on board HR camera was 2.36 m. However, the accuracies of the on-board GPS receiver and star tracker were very limited due to the technical restrictions. The accuracy of direct geo-referencing by the on-board measurements of position and attitude parameters was about 1 kilometre, which restrained the wide applications of the CBERS-02B imagery in the surveying and mapping field. It is necessary to perform the bundle block adjustment to improve the accuracy of geo-referencing. A proper sensor model has to be adopted during the bundle block adjustment using strict physical sensor model with long orbit data, in order to solve the problem of too many unknown exterior orientation parameters (EOPs). Several sensor models have been discussed, such as quadratic polynomial model, systematic error compensation model, orientation image model, and piecewise polynomial model. The combination of the systematic error compensation model and the orientation image model will be used to deal with the CBERS-02B imagery in this paper. Furthermore, three TDI-CCD linear arrays were fixed on the focal plane of the HR camera. The middle CCD array was shifted against the left and the right one. The level 1A image used in this paper was mosaicked by the three sub-images collected by the left, the middle and the right CCD, respectively. But there were some displacements among the three sub-images in the mosaicked image and the three CCD arrays may not be rigorously parallel. The angular parameter α and the translation parameters χ, γ of each CCD refer to the theoretical position on the focal plane is used to model the interior distortions, so there are totally 9 interior distortion parameters, although some of them are not significant. The laboratory calibrated parameters of the image sensor are usually different from the true values after launch. So a self-calibration strategy should be applied in the bundle block adjustment. Plenty of automatically matched GCPs with precision of 10 meters in plane and 20 meters in height are used to perform the bundle adjustment. Both the systematic error compensation model and the orientation image model with the interior selfcalibration parameters are used in the bundle block adjustment to eliminate the systematic errors caused by the camera internal distortions and to improve the precision of geo-referencing. A best combination of interior orientation parameters (IOPs) is drawn from the adjustment results with different combinations of these IOPs. Besides, there may be some gross errors in the automatically matched GCPs. The gross errors among GCPs may lead to unusual variation of the exterior orientation elements by time. Methods of enlarging the intervals of orientation image and increasing the weights of the position and attitude observations are applied in the combined bundle block adjustment to remove the influence of gross errors of GCPs. The preliminary experimental results show that for longer than 1000 km orbit data, the average accuracy of self-calibrated bundle block adjustment combined with GPS and star tracker observations is 2 pixels better than that without self-calibration. The planar position accuracies in X and Y of check points are 8 m and 7 m respectively.

INTEGRATED GEOREFERENCING OF STEREO IMAGE SEQUENCES CAPTURED WITH A STEREOVISION MOBILE MAPPING SYSTEM – APPROACHES AND PRACTICAL RESULTS

Abstract. Stereovision based mobile mapping systems enable the efficient capturing of directly georeferenced stereo pairs. With today's camera and onboard storage technologies imagery can be captured at high data rates resulting in dense stereo sequences. These georeferenced stereo sequences provide a highly detailed and accurate digital representation of the roadside environment which builds the foundation for a wide range of 3d mapping applications and image-based geo web-services. Georeferenced stereo images are ideally suited for the 3d mapping of street furniture and visible infrastructure objects, pavement inspection, asset management tasks or image based change detection. As in most mobile mapping systems, the georeferencing of the mapping sensors and observations – in our case of the imaging sensors – normally relies on direct georeferencing based on INS/GNSS navigation sensors. However, in urban canyons the achievable direct georeferencing accuracy of the dynamically captured stereo image sequences is often insufficient or at least degraded. Furthermore, many of the mentioned application scenarios require homogeneous georeferencing accuracy within a local reference frame over the entire mapping perimeter. To achieve these demands georeferencing approaches are presented and cost efficient workflows are discussed which allows validating and updating the INS/GNSS based trajectory with independently estimated positions in cases of prolonged GNSS signal outages in order to increase the georeferencing accuracy up to the project requirements.