本文選題：衛(wèi)星識別　切入點：局部構(gòu)件　出處：《哈爾濱工業(yè)大學》2017年碩士論文　論文類型：學位論文

【摘要】：目前,針對以衛(wèi)星為主的重要太空資源與設施的攻擊、保護和在軌服務已成為世界各國航天技術(shù)的重要發(fā)展方向,而衛(wèi)星識別技術(shù)是其中的關鍵環(huán)節(jié)。而飛行器抵近技術(shù)的日益成熟,使得利用天基平臺對太空目標進行高分辨率光學成像成為可能,這對衛(wèi)星識別特別是局部構(gòu)件的精確識別也提出了更新更高的需求。然而,盡管國內(nèi)外在天基目標探測識別方面的研究較多,但多集中在遠距離情況下的點目標探測及在軌運動狀態(tài)的識別方面,針對衛(wèi)星本體、太陽帆板等重要構(gòu)件的識別方面的研究罕有報道。本論文針對該問題,開展典型衛(wèi)星局部構(gòu)件光學特性及其聚類特征與參數(shù)化表征方法研究,在此基礎上研究復雜太空環(huán)境下的目標局部構(gòu)件識別方法與算法,并開展實驗驗證。主要研究工作與成果如下:(1)建立衛(wèi)星典型局部構(gòu)件的參數(shù)化表征方法與聚類模型。針對不同類型的典型衛(wèi)星,分析了衛(wèi)星局部構(gòu)件的幾何結(jié)構(gòu)與光學特性,在此基礎上提取了用于辨識衛(wèi)星本體、太陽帆板等局部構(gòu)件的聚類特征,并研究了這些特征的參數(shù)化表征方法,同時結(jié)合衛(wèi)星先驗知識,建立了本體、太陽帆板、天線構(gòu)件的聚類參數(shù)集與聚類模型。利用該模型可實現(xiàn)局部構(gòu)件特征的分類與識別,并支持后續(xù)目標識別方法與算法研究;(2)提出衛(wèi)星典型局部構(gòu)件的識別方法與算法。結(jié)合典型衛(wèi)星先驗知識與構(gòu)件聚類模型,綜合考慮衛(wèi)星在在軌運行中成像系統(tǒng)離焦、電子學噪聲、平臺抖動等導致的圖像模糊、噪聲、對比度下降等像質(zhì)退化問題,以及太空目標與天基平臺之間復雜相對運動關系導致的目標幾何變形以及遮擋等問題,提出了基于單幀與多幀序列圖像的衛(wèi)星局部構(gòu)件識別方法及算法流程和策略,從而提出了基于單幀與多幀序列圖像的衛(wèi)星局部構(gòu)件識別算法;(3)算法實驗驗證及適用性分析。結(jié)合數(shù)字仿真和地面半物理實驗,獲取不同像質(zhì)退化程度及太空目標與天基平臺間不同相對位姿關系導致局部構(gòu)件自遮擋與互遮擋以及幾何變形條件的序列幀圖像數(shù)據(jù)。利用該數(shù)據(jù),驗證了基于單幀和多幀序列圖像的目標聚類與識別算法的準確性與適用性。
[Abstract]:At present, protection and in-orbit services have become an important development direction of space technology around the world in response to attacks on important space resources and facilities dominated by satellites. The technology of satellite identification is one of the key links, and the increasingly mature technology of aircraft approach makes it possible to use space-based platform for high-resolution optical imaging of space targets. This also puts forward a higher demand for satellite recognition, especially for the precise identification of local components. However, although there are many researches on space-based target detection and recognition at home and abroad, However, most of them are focused on the detection of point targets and the recognition of the state of motion in orbit at a long distance. There are few reports on the identification of important components such as satellite body, solar canvas and so on. The optical characteristics, clustering characteristics and parameterized characterization of typical satellite local components are studied. Based on this, the methods and algorithms of target local component identification in complex space environment are studied. The main research work and results are as follows: 1) the parameterized characterization method and clustering model of typical local satellite components are established. The geometrical structure and optical properties of local satellite components are analyzed for different types of typical satellites. On this basis, the clustering features used to identify local components such as satellite body, solar canvas and so on are extracted, and the parameterized representation method of these features is studied. At the same time, combined with the prior knowledge of satellite, the ontology and solar canvas are established. The clustering parameter set and clustering model of antenna components can be used to classify and recognize local component features. The method and algorithm of satellite typical local component recognition are proposed. Combined with the prior knowledge of typical satellite and component clustering model, the defocusing of imaging system in orbit is considered synthetically. The image quality degradation problems such as electronic noise, platform jitter, noise, contrast decline, and the geometric distortion and occlusion caused by the complex relative motion relationship between the space target and the space-based platform are discussed. This paper presents a method of local satellite component recognition based on single-frame and multi-frame sequence images, as well as its algorithm flow and strategy. The experimental verification and applicability analysis of satellite local component recognition algorithm based on single-frame and multi-frame sequence images are presented, which are combined with digital simulation and ground semi-physical experiments. The serial frame image data with different degradation degree of image quality and different position and pose relationship between space target and space-based platform resulting in local component self-occlusion and mutual occlusion and geometric deformation condition are obtained. The accuracy and applicability of the target clustering and recognition algorithm based on single frame and multi frame sequence images are verified.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：V52;TP391.41

【參考文獻】

相關期刊論文 前10條

1 智喜洋;侯晴宇;張偉;孫fE;;融合多特征的天基典型目標光學識別方法[J];哈爾濱工業(yè)大學學報;2016年10期

2 楊自興;李智;;空間目標天基光學成像觀測現(xiàn)狀研究[J];國外電子測量技術(shù);2015年10期

3 趙世湖;尹丹;竇顯輝;郭莉;;單景衛(wèi)星遙感影像目標運動信息提取技術(shù)[J];測繪學報;2015年03期

4 王衛(wèi)兵;王挺峰;郭勁;;基于雙星雙目跟蹤方式的空間目標定軌技術(shù)研究[J];光學學報;2015年01期

5 王衛(wèi)兵;王挺峰;郭勁;;星載光電捕獲跟蹤瞄準控制技術(shù)分析[J];中國光學;2014年06期

6 楊露;牛燕雄;張穎;呂建明;李建平;牛海莎;劉雯文;張月新;;星載光電成像系統(tǒng)空間目標的檢測與識別技術(shù)研究[J];激光與光電子學進展;2014年12期

7 張宇;;一種圖像確認目標的多目標跟蹤方法[J];電子測量與儀器學報;2014年06期

8 王付剛;張偉;王治樂;;基于區(qū)域網(wǎng)格化的空間目標光學特性計算方法[J];航天返回與遙感;2012年02期

9 袁艷;孫成明;黃鋒振;趙慧潔;王潛;;深空背景下空間目標紫外特性建模方法研究[J];物理學報;2011年08期

10 鮑文卓;叢明煜;張偉;程軍;曹移明;;基于面元網(wǎng)格化的空間目標光學特性計算方法[J];哈爾濱工業(yè)大學學報;2010年05期

相關博士學位論文 前1條

1 舒銳;衛(wèi)星目標識別與特征參數(shù)提取方法研究[D];哈爾濱工業(yè)大學;2010年

相關碩士學位論文 前1條

1 王智勇;衛(wèi)星任務規(guī)劃分布式協(xié)同平臺流程設計及算法研究[D];國防科學技術(shù)大學;2011年

，

本文編號：1599566