Search Results (7)

High-resolution satellite images (HRSIs) obtained from onboard satellite linear array cameras suffer from geometric disturbance in the presence of attitude jitter. Therefore, detection and compensation of satellite attitude jitter are crucial to reduce the geopositioning error and to improve the geometric accuracy of HRSIs. In this work, a generative adversarial network (GAN) architecture is proposed to automatically learn and correct the deformed scene features from a single remote sensing image. In the proposed GAN, a convolutional neural network (CNN) is designed to discriminate the inputs, and another CNN is used to generate so-called fake inputs. To explore the usefulness and effectiveness of a GAN for jitter detection, the proposed GANs are trained on part of the PatternNet dataset and tested on three popular remote sensing datasets, along with a deformed Yaogan-26 satellite image. Several experiments show that the proposed model provides competitive results. The proposed GAN reveals the enormous potential of GAN-based methods for the analysis of attitude jitter from remote sensing images. Full article

The Gaofen-3 satellite is the first SAR satellite independently developed in China that achieves interferometric imaging and measurement, which improves upon Chinese civil SAR satellite data. To verify the ability of the Gaofen-3 satellite’s InSAR technology, we acquired data from Dengfeng, China, to evaluate the application and accuracy of an InSAR terrain survey. To reduce the effects introduced by data processing of Gaofen-3 data, high-accuracy InSAR image pair co-registration and phase filtering methods were adopted. Six GCPs data and 1:2000-scale DEM data were used to evaluate the elevation accuracy. In addition, for comparison with other satellites, we processed the dataset of the same area acquired by the non-civilian Yaogan-29 satellite with the same methods and evaluated the results. The experimental results indicated that the interferometric data of the Gaofen-3 satellite can achieve an accuracy of higher than 4 m of interferometric height measurement. Therefore, it will have broad prospects in the domestic InSAR application. Our research provides a certain value for the reference of the development of InSAR sensors in China. Full article

In recent years, China has launched YaoGan-13 and GaoFen-3, high-resolution synthetic aperture radar (SAR) satellites that can acquire global high-resolution images. The absolute positioning accuracy of such satellites is important for mapping areas without ground reference points and for automated processing. However, satellites without geometric calibration have poor absolute positioning accuracy, greatly restricting their application (e.g., land resource surveys). Therefore, they cannot meet national demands for high-resolution SAR images with good geometric accuracy. Here, we propose a series of methods to improve the absolute positioning accuracy of YaoGan-13 and GaoFen-3, such as the multiple-image combined calibration strategy and geometric calibration model for a real continuously moving configuration, including consideration of atmospheric propagation delay. Using high-accuracy ground control data collected from different areas, the 2-D and 3-D absolute positioning accuracies of YaoGan-13 and GaoFen-3 were assessed after implementation of the improvement measures. Experimental results showed that, after calibration, the 2-D absolute positioning accuracy of YaoGan-13 and GaoFen-3 are improved from 43.86 m to 2.57 m and from 30.34 m to 4.29 m, respectively. In addition, the 3-D absolute positioning accuracies of YaoGan-13 in plane and elevation are 3.21 m and 2.22 m, respectively. Improving the absolute positioning accuracy of these satellites could broaden the scope of their potential applications in the future. Full article

The low-cost single-frequency GNSS receiver is one of the most economical and affordable tools for the onboard real-time navigation of numerous remote sensing small/micro satellites. We concentrate on the algorithm and experiments of onboard real-time orbit determination (RTOD) based on a single-frequency GPS/BDS receiver. Through various experiments of processing the real single-frequency GPS/BDS measurements from the Yaogan-30 (YG30) series and FengYun-3C (FY3C) satellites of China, some critical aspects of the onboard RTOD are investigated, such as the optimal force models setting, the effect of different measurements, and the impact of GPS/BDS fusion. The results demonstrate that a gravity model truncated to 55 × 55 order/degree for YG30 and 45 × 45 for FY3C and compensated with an optimal stochastic modeling of empirical accelerations, which minimize the onboard computational load and only result in a slight loss of orbit accuracy, is sufficient to obtain high-precision real-time orbit results. Under the optimal force models, the real-time orbit accuracy of 0.4–0.7 m for position and 0.4–0.7 mm/s for velocity is achievable with the carrier-phase-based solution, while an inferior real-time orbit accuracy of 0.8–1.6 m for position and 0.9–1.7 mm/s for velocity is achieved with the pseudo-range-based solution. Furthermore, although the GPS/BDS fusion only makes little change to the orbit accuracy, it increases the number of visible GNSS satellites significantly, and thus enhances the geometric distribution of GNSS satellites that help suppress the local orbit errors and improves the reliability and availability of the onboard RTOD, especially in some anomalous arcs where only a few GPS satellites are trackable. Full article

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. Full article

The atmospheric propagation delay of radar signals is a systematic error that occurs in the atmospheric environment, and is a key issue in the high-precision geometric calibration of spaceborne SAR. A multimode hybrid geometric calibration method for spaceborne SAR that considers the atmospheric propagation delay is proposed in this paper. Error sources that affect the accuracy of the geometric calibration were systematically analyzed. Based on correction of the atmospheric propagation delay, a geometric calibration model for spaceborne SAR was established. The high precision geometric calibration scheme for spaceborne SAR was explored by considering the pulse-width and bandwidth of the signal. A series of experiments were carried out based on high-resolution Yaogan 13 (YG-13) SAR satellite data and ground control data. The experimental results demonstrated that the proposed method is effective. The plane positioning accuracy of YG-13 in stripmap mode without control points is better than 3 m, and the accuracy of the sliding spotlight mode is better than 1.5 m. Full article

Satellite attitude accuracy is an important factor affecting the geometric processing accuracy of high-resolution optical satellite imagery. To address the problem whereby the accuracy of the Yaogan-24 remote sensing satellite’s on-board attitude data processing is not high enough and thus cannot meet its image geometry processing requirements, we developed an approach involving on-ground attitude data processing and digital orthophoto (DOM) and the digital elevation model (DEM) verification of a geometric calibration field. The approach focuses on three modules: on-ground processing based on bidirectional filter, overall weighted smoothing and fitting, and evaluation in the geometric calibration field. Our experimental results demonstrate that the proposed on-ground processing method is both robust and feasible, which ensures the reliability of the observation data quality, convergence and stability of the parameter estimation model. In addition, both the Euler angle and quaternion could be used to build a mathematical fitting model, while the orthogonal polynomial fitting model is more suitable for modeling the attitude parameter. Furthermore, compared to the image geometric processing results based on on-board attitude data, the image uncontrolled and relative geometric positioning result accuracy can be increased by about 50%. Full article