Due to the consideration of safety,non-contact measurement methods are be-coming more acceptable.However,massive measurement will bring high labor-cost and low working efficiency.To address these limitations,this pape...Due to the consideration of safety,non-contact measurement methods are be-coming more acceptable.However,massive measurement will bring high labor-cost and low working efficiency.To address these limitations,this paper introduces a deep learning model for the antenna attitude parameter measurement,which can be divided into an an-tenna location phase and a calculation phase of the attitude parameter.In the first phase,a single shot multibox detector(SSD)is applied to automatically recognize and discover the antenna from pictures taken by drones.In the second phase,the located antennas’fea-ture lines are extracted and their attitude parameters are then calculated mathematically.Experiments show that the proposed algorithms outperform existing related works in effi-ciency and accuracy,and therefore can be effectively used in engineering applications.展开更多
文摘Due to the consideration of safety,non-contact measurement methods are be-coming more acceptable.However,massive measurement will bring high labor-cost and low working efficiency.To address these limitations,this paper introduces a deep learning model for the antenna attitude parameter measurement,which can be divided into an an-tenna location phase and a calculation phase of the attitude parameter.In the first phase,a single shot multibox detector(SSD)is applied to automatically recognize and discover the antenna from pictures taken by drones.In the second phase,the located antennas’fea-ture lines are extracted and their attitude parameters are then calculated mathematically.Experiments show that the proposed algorithms outperform existing related works in effi-ciency and accuracy,and therefore can be effectively used in engineering applications.
