Several noteworthy breakthroughs have been made with the BeiDou Navigation Satellite System (BDS) and other global navigation satellite systems as well as the associated augmentation systems, such as the commissioning of the BDS-3 preliminary system and the successful launch of the first BDS-3 GEO satellite which carries the satellitebased augmentation payload. Presently, BDS can provide basic services globally, and its augmentation system is also being tested. This paper gives an overview of BDS and satellite navigation augmentation technologies. This overview is divided into four parts, which include the system segment technologies, satellite segment technologies, propagation segment technologies, and user segment technologies. In each part, these technologies are described from the perspectives of preliminary information, research progress, and summary. Moreover, the significance and progress of the BeiDou Satellite-based Augmentation System (BDSBAS), low earth orbit augmentation, and the national BeiDou ground-based augmentation system are presented, along with the airborne-based augmentation system. Furthermore, the conclusions and discussions covering popular topics for research, frontiers in research and development, achievements, and suggestions are listed for future research.
Addressing the problems of visual surveillance for anti-UAV, a new flying small target detection method is proposed based on Gaussian mixture background modeling in a compressive sensing domain and low-rank and sparse matrix decomposition of local image. First of all, images captured by stationary visual sensors are broken into patches and the candidate patches which perhaps contain targets are identified by using a Gaussian mixture background model in a compressive sensing domain. Subsequently, the candidate patches within a finite time period are separated into background images and target images by low-rank and sparse matrix decomposition. Finally, flying small target detection is achieved over separated target images by threshold segmentation. The experiment results using visible and infrared image sequences of flying UAV demonstrate that the proposed methods have effective detection performance and outperform the baseline methods in precision and recall evaluation.
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