Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the see...Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the seekers the FOV is not fully exploited which means the target can be missed before becoming out of the FOV,this results of the nonlinearity of the reticle structure.In this paper,a novel method of the target position detection a crossed four slits or crossed array trackers(CAT) seeker will be designed,simulated and evaluated.The idea of this method depends on dividing the FOV into main regions up to a certain parameter,which is the pulses number;then,each main region will be divided into sub-regions up to a second parameter which will be the pulses distribution a spin period.The errors sources will be discussed and evaluated.Other new idea will be applied which is exploiting some area of the FOV where a part of the position data is missed in the information signal by pushing the target to the region where the information signal carries the total position data.展开更多
Abstract:Sparse coding(SC)based visual tracking(l1-tracker)is gaining increasing attention,and many related algorithms are developed.In these algorithms,each candidate region is sparsely represented as a set of target...Abstract:Sparse coding(SC)based visual tracking(l1-tracker)is gaining increasing attention,and many related algorithms are developed.In these algorithms,each candidate region is sparsely represented as a set of target templates.However,the structure connecting these candidate regions is usually ignored.Lu proposed an NLSSC-tracker with non-local self-similarity sparse coding to address this issue,which has a high computational cost.In this study,we propose an Euclidean local-structure constraint based sparse coding tracker with a smoothed Euclidean local structure.With this tracker,the optimization procedure is transformed to a small-scale l1-optimization problem,significantly reducing the computational cost.Extensive experimental results on visual tracking demonstrate the eectiveness and efficiency of the proposed algorithm.展开更多
文摘Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the seekers the FOV is not fully exploited which means the target can be missed before becoming out of the FOV,this results of the nonlinearity of the reticle structure.In this paper,a novel method of the target position detection a crossed four slits or crossed array trackers(CAT) seeker will be designed,simulated and evaluated.The idea of this method depends on dividing the FOV into main regions up to a certain parameter,which is the pulses number;then,each main region will be divided into sub-regions up to a second parameter which will be the pulses distribution a spin period.The errors sources will be discussed and evaluated.Other new idea will be applied which is exploiting some area of the FOV where a part of the position data is missed in the information signal by pushing the target to the region where the information signal carries the total position data.
基金National Natural Foundation of China under Grant(61572085,61502058)
文摘Abstract:Sparse coding(SC)based visual tracking(l1-tracker)is gaining increasing attention,and many related algorithms are developed.In these algorithms,each candidate region is sparsely represented as a set of target templates.However,the structure connecting these candidate regions is usually ignored.Lu proposed an NLSSC-tracker with non-local self-similarity sparse coding to address this issue,which has a high computational cost.In this study,we propose an Euclidean local-structure constraint based sparse coding tracker with a smoothed Euclidean local structure.With this tracker,the optimization procedure is transformed to a small-scale l1-optimization problem,significantly reducing the computational cost.Extensive experimental results on visual tracking demonstrate the eectiveness and efficiency of the proposed algorithm.
