视频卫星稳像是实现卫星视频高精度应用的前提和基础。由于卫星姿态指向精度不足以及平台姿态稳定度不足等原因,通常需要引入基于图像配准的稳像技术以实现视频凝视的效果;然而在观测海上目标时,由于没有控制点标校,帧间无法开展基于特...视频卫星稳像是实现卫星视频高精度应用的前提和基础。由于卫星姿态指向精度不足以及平台姿态稳定度不足等原因,通常需要引入基于图像配准的稳像技术以实现视频凝视的效果;然而在观测海上目标时,由于没有控制点标校,帧间无法开展基于特征点的配准,所以天基凝视视频相机在观测时经常会出现目标在像面上反复跳变的问题。提出一种基于海上多目标舰船检测的全局前景视频稳像GFVS(global foreground video stabilization)方法,构建高斯误差模型,通过优化后位置和原始位置的偏差修正像面错位,最后进行稳像视频合成。实验结果表明,该方法能够有效解决海上控制点不足时抖动图像难以配准的问题,得到更加稳定的凝视视频效果,应用吉林一号卫星星座采集的两组卫星数据进行验证实验,最终稳像的误差能够控制在0.9个像素以内。展开更多
The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper coo...The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.展开更多
文摘视频卫星稳像是实现卫星视频高精度应用的前提和基础。由于卫星姿态指向精度不足以及平台姿态稳定度不足等原因,通常需要引入基于图像配准的稳像技术以实现视频凝视的效果;然而在观测海上目标时,由于没有控制点标校,帧间无法开展基于特征点的配准,所以天基凝视视频相机在观测时经常会出现目标在像面上反复跳变的问题。提出一种基于海上多目标舰船检测的全局前景视频稳像GFVS(global foreground video stabilization)方法,构建高斯误差模型,通过优化后位置和原始位置的偏差修正像面错位,最后进行稳像视频合成。实验结果表明,该方法能够有效解决海上控制点不足时抖动图像难以配准的问题,得到更加稳定的凝视视频效果,应用吉林一号卫星星座采集的两组卫星数据进行验证实验,最终稳像的误差能够控制在0.9个像素以内。
基金Project(61801495)supported by the National Natural Science Foundation of China
文摘The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.
