西北工业大学学报
西北工業大學學報
서북공업대학학보
JOURNAL OF NORTHWESTERN POLYTECHNICAL UNIVERSITY
2014年
2期
227-234
,共8页
李少毅%董敏周%陈康%张凯%闫杰
李少毅%董敏週%陳康%張凱%閆傑
리소의%동민주%진강%장개%염걸
空间多路%重叠成像%目标跟踪%重叠编码
空間多路%重疊成像%目標跟蹤%重疊編碼
공간다로%중첩성상%목표근종%중첩편마
algorithms%computer simulation%decoding%encoding( symbols)%lenses%imaging systems%location%pixels%target tracking%spatially multiplexed superposition imaging%overlap encoding
针对传统成像系统大视场连续跟踪的问题,提出一种新的基于空间多路重叠成像技术的可直接判定宽视场中目标位置的目标跟踪方法,以实现大范围持久监视及多目标跟踪。首先,分析了多路成像探测、跟踪机理,提出利用球面透镜阵列设计一种空间多路、共焦平面、宽视场凝视成像系统结构,各透镜单元对应的视场之间有特定的空间重叠编码关系,以便同时成像之后解算目标位置。其次,重点研究了运动多目标解码跟踪原理,在提取所有重叠空间目标像点后,按照位置和速度判断准则对重叠空间目标像点进行分类,然后在这个分类集合上解码目标所在位置。最后,对目标解码算法做了仿真,结果表明,此方法能很好地实现在宽视场中对目标的解码跟踪。
針對傳統成像繫統大視場連續跟蹤的問題,提齣一種新的基于空間多路重疊成像技術的可直接判定寬視場中目標位置的目標跟蹤方法,以實現大範圍持久鑑視及多目標跟蹤。首先,分析瞭多路成像探測、跟蹤機理,提齣利用毬麵透鏡陣列設計一種空間多路、共焦平麵、寬視場凝視成像繫統結構,各透鏡單元對應的視場之間有特定的空間重疊編碼關繫,以便同時成像之後解算目標位置。其次,重點研究瞭運動多目標解碼跟蹤原理,在提取所有重疊空間目標像點後,按照位置和速度判斷準則對重疊空間目標像點進行分類,然後在這箇分類集閤上解碼目標所在位置。最後,對目標解碼算法做瞭倣真,結果錶明,此方法能很好地實現在寬視場中對目標的解碼跟蹤。
침대전통성상계통대시장련속근종적문제,제출일충신적기우공간다로중첩성상기술적가직접판정관시장중목표위치적목표근종방법,이실현대범위지구감시급다목표근종。수선,분석료다로성상탐측、근종궤리,제출이용구면투경진렬설계일충공간다로、공초평면、관시장응시성상계통결구,각투경단원대응적시장지간유특정적공간중첩편마관계,이편동시성상지후해산목표위치。기차,중점연구료운동다목표해마근종원리,재제취소유중첩공간목표상점후,안조위치화속도판단준칙대중첩공간목표상점진행분류,연후재저개분류집합상해마목표소재위치。최후,대목표해마산법주료방진,결과표명,차방법능흔호지실현재관시장중대목표적해마근종。
The traditional imaging system has some difficulty in tracking targets continuously over a large field of view. Therefore, we propose what we believe to be a novel multi-target tracking method that uses spatially multi-plexed superposition imaging, with which multiple targets can be directly located in a wide field of view, thus a-chieving a wide range of persistent surveillance and multi-target tracking. Then we design a staring imaging architec-ture with spatially multiplexed, confocal plane and wide field of view by using the spherical lens array;the staring imaging architecture we designed has overlap encoding relationship among the subfields of view of the lens unit so as to calculate the position of the target after simultaneous imaging. After analyzing the multiplexed imaging detection and tracking principles, we extract the pixels of all spatially superposed images of moving multi-targets and classify them according to their location and velocity judgment criteria and then decode the target location with the classifi-cation set. Finally we simulate the target decoding algorithm; the simulation results, given in Tables 1 and 2 and Figs. 5 through 8, and their analysis show preliminarily that our multi-target tracking method can effectively decode and track multiple targets in a wide field of view.