At present, the main problem faced by ground-based augment system （GBAS） is that though carder smoothing filter and local differential global positioning system （LDGPS） improve the accuracy of the pseudorange by r...At present, the main problem faced by ground-based augment system （GBAS） is that though carder smoothing filter and local differential global positioning system （LDGPS） improve the accuracy of the pseudorange by reducing the noise in it and eliminating almost all the common errors between the user and the reference station, they also cause extra errors on account of the effects of the ionosphere temporal and spatial gradients. Based on the analysis of these errors as well as the smoothing noise, this article suggests a new algorithm to design the optimal Hatch filter, whose smoothing window width varies real-time with the satellite elevation, ionosphere variation, and distance from the user to the reference station. By conducting the positioning process in the GBAS emulation platform for several hours and after its comparison with the performances of traditional Hatch filters, it is found that the errors in the differential correction become smaller and the positioning accuracy gets heightened with this new method.展开更多
Visual tracking is an important area in computer vision. How to deal with illumination and occlusion problems is a challenging issue. This paper presents a novel and efficient tracking algorithm to handle such problem...Visual tracking is an important area in computer vision. How to deal with illumination and occlusion problems is a challenging issue. This paper presents a novel and efficient tracking algorithm to handle such problems. On one hand, a target＇s initial appearance always has clear contour, which is light-invariant and robust to illumination change. On the other hand, features play an important role in tracking, among which convolutional features have shown favorable performance. Therefore, we adopt convolved contour features to represent the target appearance. Generally speaking, first-order derivative edge gradient operators are efficient in detecting contours by convolving them with images. Especially, the Prewitt operator is more sensitive to horizontal and vertical edges, while the Sobel operator is more sensitive to diagonal edges. Inherently, Prewitt and Sobel are complementary with each other. Technically speaking, this paper designs two groups of Prewitt and Sobel edge detectors to extract a set of complete convolutional features, which include horizontal, vertical and diagonal edges features. In the first frame, contour features are extracted from the target to construct the initial appearance model. After the analysis of experimental image with these contour features, it can be found that the bright parts often provide more useful information to describe target characteristics. Therefore, we propose a method to compare the similarity between candidate sample and our trained model only using bright pixels, which makes our tracker able to deal with partial occlusion problem. After getting the new target, in order to adapt appearance change, we propose a corresponding online strategy to incrementally update our model. Experiments show that convolutional features extracted by well-integrated Prewitt and Sobel edge detectors can be eff^cient enough to learn robust appearance model. Numerous experimental results on nine challenging sequences show that our proposed approach is very effective and robust in comp展开更多
基金National Natural Science Foundation of China (60672181)National High-tech Research and Development Program (2006AA12A101)
文摘At present, the main problem faced by ground-based augment system （GBAS） is that though carder smoothing filter and local differential global positioning system （LDGPS） improve the accuracy of the pseudorange by reducing the noise in it and eliminating almost all the common errors between the user and the reference station, they also cause extra errors on account of the effects of the ionosphere temporal and spatial gradients. Based on the analysis of these errors as well as the smoothing noise, this article suggests a new algorithm to design the optimal Hatch filter, whose smoothing window width varies real-time with the satellite elevation, ionosphere variation, and distance from the user to the reference station. By conducting the positioning process in the GBAS emulation platform for several hours and after its comparison with the performances of traditional Hatch filters, it is found that the errors in the differential correction become smaller and the positioning accuracy gets heightened with this new method.
基金This paper is supported by the National Natural Science Foundation of China under Grant No. 61472289 and the National Key Research and Development Project of China under Grant No. 2016YFC0106305.
文摘Visual tracking is an important area in computer vision. How to deal with illumination and occlusion problems is a challenging issue. This paper presents a novel and efficient tracking algorithm to handle such problems. On one hand, a target＇s initial appearance always has clear contour, which is light-invariant and robust to illumination change. On the other hand, features play an important role in tracking, among which convolutional features have shown favorable performance. Therefore, we adopt convolved contour features to represent the target appearance. Generally speaking, first-order derivative edge gradient operators are efficient in detecting contours by convolving them with images. Especially, the Prewitt operator is more sensitive to horizontal and vertical edges, while the Sobel operator is more sensitive to diagonal edges. Inherently, Prewitt and Sobel are complementary with each other. Technically speaking, this paper designs two groups of Prewitt and Sobel edge detectors to extract a set of complete convolutional features, which include horizontal, vertical and diagonal edges features. In the first frame, contour features are extracted from the target to construct the initial appearance model. After the analysis of experimental image with these contour features, it can be found that the bright parts often provide more useful information to describe target characteristics. Therefore, we propose a method to compare the similarity between candidate sample and our trained model only using bright pixels, which makes our tracker able to deal with partial occlusion problem. After getting the new target, in order to adapt appearance change, we propose a corresponding online strategy to incrementally update our model. Experiments show that convolutional features extracted by well-integrated Prewitt and Sobel edge detectors can be eff^cient enough to learn robust appearance model. Numerous experimental results on nine challenging sequences show that our proposed approach is very effective and robust in comp
