In response to the downlink synchronization requirements of the user equipment(UE)or third-party radio equipment in fifth-generation(5G)mobile communication systems,a synchronization algorithm of primary synchroni-zat...In response to the downlink synchronization requirements of the user equipment(UE)or third-party radio equipment in fifth-generation(5G)mobile communication systems,a synchronization algorithm of primary synchroni-zation signal(PSS)was designed and developed in the 5G system based on block cross-correlation.According to the new characteristics of the 5G synchronization channel and broadcast channel,starting from the traditional downlink synchronization algorithm of long-term evolution(LTE),the detection performance of the algorithm under a low signal-to-noise ratio(SNR)is improved by introducing an incoherent accumulation,and the new scheme of joint coarse frequency offset estimation is used to improve the frequency offset estimation performance.Finally,the performance of the proposed synchronization algorithm is verified by conducting a simulation on a 5G downlink simulation platform based on MATLAB software.Simulation results show that the improved downlink synchronization algorithm has stable performance in the tapped delay line-C(TDL-C)and additive white Gaussian noise(AWGN)channels with large frequency deviation and low SNR.展开更多
A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow ...A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.展开更多
基金The Social Development Projects of Jiangsu Science and Technology Department(No.BE2018704).
文摘In response to the downlink synchronization requirements of the user equipment(UE)or third-party radio equipment in fifth-generation(5G)mobile communication systems,a synchronization algorithm of primary synchroni-zation signal(PSS)was designed and developed in the 5G system based on block cross-correlation.According to the new characteristics of the 5G synchronization channel and broadcast channel,starting from the traditional downlink synchronization algorithm of long-term evolution(LTE),the detection performance of the algorithm under a low signal-to-noise ratio(SNR)is improved by introducing an incoherent accumulation,and the new scheme of joint coarse frequency offset estimation is used to improve the frequency offset estimation performance.Finally,the performance of the proposed synchronization algorithm is verified by conducting a simulation on a 5G downlink simulation platform based on MATLAB software.Simulation results show that the improved downlink synchronization algorithm has stable performance in the tapped delay line-C(TDL-C)and additive white Gaussian noise(AWGN)channels with large frequency deviation and low SNR.
基金Project(50778015)supported by the National Natural Science Foundation of ChinaProject(2012CB725403)supported by the Major State Basic Research Development Program of China
文摘A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.
