本文關(guān)鍵詞：軍事信息系統(tǒng)中信息融合關(guān)鍵技術(shù)研究　出處：《電子科技大學(xué)》2016年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 信息融合 認(rèn)知機(jī)制 特征提取 內(nèi)部模型 目標(biāo)識(shí)別與跟蹤

【摘要】：軍事信息系統(tǒng)是用來在整個(gè)軍事作戰(zhàn)范圍內(nèi)支持指揮官籌劃、決策、指揮作戰(zhàn)等為一體的指揮控制平臺(tái),是軍隊(duì)?wèi)?zhàn)斗力的“倍增器”。它是對各軍兵種所使用的信息系統(tǒng)進(jìn)行綜合設(shè)計(jì)、綜合集成和綜合運(yùn)用,是信息系統(tǒng)、武器系統(tǒng)和軍事保障系統(tǒng)的粘合劑。信息活動(dòng)的描述、融合是軍事信息系統(tǒng)動(dòng)態(tài)要素建模、分析與仿真的基礎(chǔ)。但是,從信息融合角度對軍事信息系統(tǒng)的研究,當(dāng)前國內(nèi)外尚未見到比較系統(tǒng)的研究成果。本文研究的總目標(biāo)是探究人腦信息融合的認(rèn)知機(jī)制,研究其內(nèi)在組網(wǎng)、特征提取、信息融合、知識(shí)表達(dá)和推理、決策等認(rèn)知機(jī)理,并將研究結(jié)果應(yīng)用于現(xiàn)代軍事系統(tǒng)中多傳感器目標(biāo)跟蹤與信息融合過程中。從認(rèn)知科學(xué)的角度為軍事信息系統(tǒng)應(yīng)用背景下目標(biāo)監(jiān)測和信息融合,得出有效的融合策略提供指導(dǎo)或者參考。研究工作與創(chuàng)新點(diǎn)主要體現(xiàn)在以下四個(gè)方面:一、提出了一種基于內(nèi)部模型驅(qū)動(dòng)的融合進(jìn)化結(jié)構(gòu)體系理論方案。人的大腦處理信息過程是一種復(fù)雜的信息融合過程,其構(gòu)建在一種智能、靈活的多源信息融合進(jìn)化結(jié)構(gòu)體系基礎(chǔ)上。本文在借鑒人腦研究的相關(guān)理論基礎(chǔ)上,通過對比多源信息融合進(jìn)化過程與人腦的信息融合的模型、機(jī)制,指出大腦存在是由大量局部神經(jīng)元構(gòu)成的局部神經(jīng)元回路,由此提出了一個(gè)很重要的概念:融合元;并通過研究發(fā)現(xiàn)多源信息融合系統(tǒng)的進(jìn)化過程與分布式的神經(jīng)網(wǎng)絡(luò)體系結(jié)構(gòu)具有很多相似特點(diǎn),由此提出了一種基于內(nèi)部模型驅(qū)動(dòng)的融合進(jìn)化結(jié)構(gòu)體系理論方案。最后,從理論解析和現(xiàn)代軍事應(yīng)用背景下仿真實(shí)驗(yàn)證實(shí),基于內(nèi)部模型驅(qū)動(dòng)的多源信息融合系統(tǒng)進(jìn)化體系結(jié)構(gòu)將大大提高作戰(zhàn)效能和戰(zhàn)時(shí)應(yīng)變能力。二、提出了適應(yīng)于戰(zhàn)場感知信息融合的智能化分布式系統(tǒng)組網(wǎng)方法�，F(xiàn)代戰(zhàn)爭中智能化裝備的使用以及對信息處理能力的需求的不斷提高,網(wǎng)絡(luò)中心戰(zhàn)環(huán)境逐步實(shí)現(xiàn)智能化組網(wǎng)的需求變得越來越迫切。從本質(zhì)上說,網(wǎng)絡(luò)中心戰(zhàn)環(huán)境的戰(zhàn)場感知,是通過有效地連接戰(zhàn)場空間中知識(shí)實(shí)體節(jié)點(diǎn)將信息優(yōu)勢轉(zhuǎn)化為戰(zhàn)斗力,而任何一個(gè)空間中知識(shí)實(shí)體節(jié)點(diǎn),都可以在條件合適的情況下產(chǎn)生一次信息融合事件,通過請求網(wǎng)絡(luò)系統(tǒng)資源的協(xié)作,實(shí)現(xiàn)多傳感器、智能接口的資源共享和信息交流,這使得信息之間的相關(guān)性、冗余性,以及統(tǒng)計(jì)分布特性等變得更加復(fù)雜和難以確定。由此,本文提出了智能化分布式系統(tǒng)組網(wǎng)方法,通過分布協(xié)作式調(diào)度網(wǎng)絡(luò)中各融合元,融合元節(jié)點(diǎn)相互之間進(jìn)行協(xié)調(diào)來做出決策,達(dá)到共同完成信息資源調(diào)度融合任務(wù)的目的。實(shí)驗(yàn)表明,分布式系統(tǒng)組網(wǎng)方法更適合融合節(jié)點(diǎn)獲取戰(zhàn)場信息。三、提出一種可以用于多傳感器目標(biāo)監(jiān)測的融合非統(tǒng)計(jì)方法,即表決融合。適應(yīng)于網(wǎng)絡(luò)中心戰(zhàn)環(huán)境的戰(zhàn)場信息類型雜、信息源多、信息量巨大、信息質(zhì)量差且富含誘騙,要從這樣的信息環(huán)境中快速、準(zhǔn)確、完整地提取出指揮員所需要的戰(zhàn)場態(tài)勢和環(huán)境圖景來,難度極大,需要解決的問題極多。由此,提出了利用分布式網(wǎng)絡(luò)多傳感器監(jiān)測目標(biāo)的結(jié)果,來綜合得出目標(biāo)是否存在的判決技術(shù),應(yīng)用于目標(biāo)身份信息融合的不確定性推理技術(shù),提出一種簡單的非統(tǒng)計(jì)方法,即表決融合,它可以用于多傳感器目標(biāo)監(jiān)測的融合。實(shí)驗(yàn)表明:應(yīng)用表決融合可獲得高的節(jié)點(diǎn)感知性能。四、提出了一種能提高傳感器組網(wǎng)的發(fā)現(xiàn)能力和連續(xù)觀測能力的多傳感器自適應(yīng)狀態(tài)融合技術(shù)。自適應(yīng)狀態(tài)融合技術(shù)著眼于算法間的互補(bǔ)性達(dá)到某種優(yōu)化,算法能夠根據(jù)信息源特性和目標(biāo)自動(dòng)選擇最有效算法,具有透明性和開放性,是多層次多模型的自適應(yīng)算法。實(shí)驗(yàn)證實(shí):算法提出將為指揮信息系統(tǒng)信息融合提高精度、反隱身、反低空入侵、抗丟失目標(biāo)等帶來較大好處,同時(shí)可克服傳感器性能不穩(wěn)定等缺陷。
[Abstract]:Military information system is used to support the commander in planning military operations within the scope of the decision, combat command and control platform for the integration and military battle. It is a comprehensive design information system used in various branches of integrated and comprehensive use of the information system, weapon system and adhesive the military security system. Information fusion is the description of elements of military information system based on dynamic analysis and simulation. However, research from the angle of information fusion in military information system at home and abroad, no systematic research achievements. The overall objective of this study is to explore the cognitive mechanism of human brain information fusion, research the internal network, feature extraction, information fusion, knowledge representation and reasoning, decision-making and cognitive mechanism, the research results can be applied to modern military system in multi sensor Target tracking and information fusion process. From the perspective of cognitive science as the application background of military information system monitoring and information fusion, the effective fusion strategy to provide guidance or reference. The research work and innovations are mainly embodied in the following four aspects: first, put forward a combined evolutionary scheme of internal model driven architecture theory based on the information processing of the brain. The process is a complex process of information fusion, its construction in an intelligent, flexible multi-source information fusion system based on structure evolution. Based on the related theory of human brain research, by comparing the multi-source information fusion process of evolution and the brain information fusion model, mechanism that is, the brain local neuronal circuit composed of a large number of local neurons, thus put forward a very important concept: the fusion element; and we found The neural network architecture evolution and distributed multi-source information fusion system has many similar characteristics, this paper proposes a fusion scheme of internal structure evolution theory based on model driven. Finally, from the theoretical analysis and application background of modern military simulation results confirm that the multi-source information fusion system of internal model driven architecture evolution greatly improve the combat effectiveness and adaptability. Based on the wartime two, put forward the networking method of intelligent distributed system in battlefield information fusion. The intelligent equipment in modern war and the demand for information processing capabilities continue to improve, the network centric warfare environment gradually realize the intelligent network demand has become more urgent. In essence, the battlefield environment of network centric warfare, is the letter by effectively connecting battlefield knowledge nodes in the physical space Information superiority into combat, and knowledge entity any space node can produce an information fusion event in the right conditions, through the collaboration network request system resources, to achieve multi sensor intelligent interface, resource sharing and information exchange, which makes the correlation between information redundancy, and the statistical distribution characteristics become more complicated and difficult to determine. Thus, proposed network methods of intelligent distributed systems, distributed scheduling in the network through the fusion, fusion between the element node coordinate to make decisions, to jointly complete the information fusion task to resource scheduling. The experimental results show that the network method of distributed system suitable fusion nodes acquire the battlefield information. Three, this can be used for a multi-sensor target monitoring non statistical method, which is adapted to the voting fusion. Battlefield information environment type of network centric warfare complex, many information sources, a huge amount of information, information quality is poor and rich in deception, to fast, from this information environment accurately, completely extract the battlefield to commander and environmental picture, extremely difficult, need to solve many issues. Therefore, put forward the use of distributed multi sensor monitoring target results, to get the target existence judgment technology, applied to the target identity information fusion uncertainty reasoning technology, we proposed a simple non statistical method, namely, it can be used for voting fusion, multi-sensor target monitoring. Experimental results show that the application of voting fusion can be obtained the node sensing high performance. Four, this paper presents a multi sensor adaptive state can improve the sensor network discovery ability and continuous observation ability of fusion technology. Adaptive state finance Complementary technology focuses on the algorithms to some optimization algorithm can automatically select the most effective algorithm according to the characteristics of information source and target, transparent and open, multi-level and multi model adaptive algorithm. Experiments show that the proposed algorithm for command information system to improve the accuracy of information fusion, anti stealth, anti low intrusion the anti lost goals, bring greater benefits, and can overcome the defects such as sensor performance is not stable.

【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP202;E11

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本文編號(hào)：1377675