GNSS信号的空间信号(SIS)质量直接影响用户的定位、测试和授时(Positioning,Velocity and Timing,PVT)服务精度,但由于授权信号保密等原因,授权信号的伪码序列未知,卫星导航系统授权信号质量评估存在一定的困难性。该文主要分析GPS BII...GNSS信号的空间信号(SIS)质量直接影响用户的定位、测试和授时(Positioning,Velocity and Timing,PVT)服务精度,但由于授权信号保密等原因,授权信号的伪码序列未知,卫星导航系统授权信号质量评估存在一定的困难性。该文主要分析GPS BIIF-5卫星L1频点的相干自适应副载波调制(CASM)信号,利用匹配滤波理论恢复出采集数据中的P(Y)码和M码两个授权信号分量的伪码符号,采用极大似然估计结合信号分布特点准确求解出各信号分量之间的功率分配。重点分析P(Y)码和M码信号相关性能,包含相关曲线、相关损失和S曲线过零点偏差(S-Curve bias),定量地评估了授权信号的空间信号质量。提出完整的基于GPS L1频点授权信号质量评估方法,研究成果可作为其他卫星导航系统授权信号质量评估的参考。展开更多
While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal proces...While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this paper, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D images/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.展开更多
基金partially supported by the Research Grants Council of the Hong Kong SAR, China (Project CUHK 415712)the Ministry of Education Academic Research Fund (AcRF) Tier 2 in Singapore under Grant No. T208B1218
文摘While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this paper, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D images/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.
