With the great development of unmanned aircraft system(UAS)over the last decade,sense and avoid(SAA)system has been a crucial technology for integrating unmanned aircraft vehicle(UAV)into national airspace with reliab...With the great development of unmanned aircraft system(UAS)over the last decade,sense and avoid(SAA)system has been a crucial technology for integrating unmanned aircraft vehicle(UAV)into national airspace with reliable and safe operations.This paper mainly focuses on intruder detection for SAA system.A robust algorithm based on the combination of edge-boxes and spatial pyramid matching using sparse coding(sc-SPM)is presented.The algorithm is composed of three stages.First,edge-boxes method is adopted to obtain a large number of proposals;Second,the optimization program is presented to obtain intruder area-of-interest(ROI)regions;Third,sc-SPM is employed for feature representation of ROI regions and support vector machines(SVM)is adopted to detect the intruder.The algorithm is evaluated under different weather conditions.The recall reaches to 0.95 in dawn and sunny weather and 0.9 in cloudy weather.The experimental results indicate that the intruder detection algorithm is effective and robust with various weather under complex background.展开更多
基金supported by the National Natural Science Foundation of China (Nos. 61673211, U1633105)the Fundamental Research Funds for the Central Universities of China (No. NP2019105)the Funding of Jiangsu Innovation Program for Graduation Education, Funding for Outstanding Doctoral Dissertation in NUAA (No.BCXJ18-11)
文摘With the great development of unmanned aircraft system(UAS)over the last decade,sense and avoid(SAA)system has been a crucial technology for integrating unmanned aircraft vehicle(UAV)into national airspace with reliable and safe operations.This paper mainly focuses on intruder detection for SAA system.A robust algorithm based on the combination of edge-boxes and spatial pyramid matching using sparse coding(sc-SPM)is presented.The algorithm is composed of three stages.First,edge-boxes method is adopted to obtain a large number of proposals;Second,the optimization program is presented to obtain intruder area-of-interest(ROI)regions;Third,sc-SPM is employed for feature representation of ROI regions and support vector machines(SVM)is adopted to detect the intruder.The algorithm is evaluated under different weather conditions.The recall reaches to 0.95 in dawn and sunny weather and 0.9 in cloudy weather.The experimental results indicate that the intruder detection algorithm is effective and robust with various weather under complex background.
