【摘要】：隨著微電子技術(shù)、導(dǎo)航技術(shù)、控制理論的發(fā)展,使得體積小、成本低、功耗低、功能多、精度高、可靠性高的組合導(dǎo)航系統(tǒng)成為新的發(fā)展趨勢(shì),并且廣泛應(yīng)用在軍事、航空、航天、航海、交通等領(lǐng)域。組合導(dǎo)航系統(tǒng)主要任務(wù)是為運(yùn)載體提供準(zhǔn)確可靠的位置、速度、姿態(tài)等信息。隨著自動(dòng)化程度越來越高系統(tǒng)的結(jié)構(gòu)越來越復(fù)雜,系統(tǒng)內(nèi)設(shè)備之間的聯(lián)系越來越緊密,其性能直接關(guān)系到運(yùn)載體及載體全體人員的安全。因此,通過評(píng)估系統(tǒng)的性能,為組合導(dǎo)航系統(tǒng)的優(yōu)化設(shè)計(jì)奠定基礎(chǔ),對(duì)確保系統(tǒng)高效可靠的工作具有重要意義。首先,本文以組合導(dǎo)航系統(tǒng)為例,在閱讀大量相關(guān)文獻(xiàn)的基礎(chǔ)上,介紹了課題研究的背景和意義,總結(jié)了導(dǎo)航系統(tǒng)及其評(píng)估理論的發(fā)展現(xiàn)狀,闡述了系統(tǒng)評(píng)價(jià)過程中需要注意的問題及幾種常用的系統(tǒng)評(píng)價(jià)方法,探討了組合導(dǎo)航系統(tǒng)的工作原理,分析了系統(tǒng)性能指標(biāo),建立了組合導(dǎo)航系統(tǒng)性能評(píng)估指標(biāo)體系,給出了指標(biāo)權(quán)重的確定方法,通過采用層次分析法確定了指標(biāo)權(quán)重。其次,針對(duì)層次分析法得出的指標(biāo)權(quán)重客觀性較差,模糊綜合評(píng)判法確定的評(píng)判等級(jí)可區(qū)分度不強(qiáng)等問題,運(yùn)用了基于熵的模糊綜合評(píng)判法,建立了系統(tǒng)性能評(píng)判模型,該方法運(yùn)用熵權(quán)法修正了指標(biāo)權(quán)重,選取加權(quán)平均算子進(jìn)行模糊運(yùn)算,根據(jù)指標(biāo)權(quán)重使得每個(gè)指標(biāo)對(duì)系統(tǒng)的綜合性能都有所體現(xiàn),采用區(qū)間量化方式增強(qiáng)了處于同一評(píng)判等級(jí)系統(tǒng)的可區(qū)分性,通過仿真實(shí)驗(yàn)證明了該方法可以準(zhǔn)確、客觀的評(píng)估出系統(tǒng)的性能,并與模糊層次分析法進(jìn)行了比較分析。然后,針對(duì)組合導(dǎo)航系統(tǒng)性能評(píng)價(jià)的非線性和復(fù)雜性問題,BP神經(jīng)網(wǎng)絡(luò)對(duì)非線性系統(tǒng)有較強(qiáng)適應(yīng)能力,運(yùn)用了基于BP神經(jīng)網(wǎng)絡(luò)的綜合評(píng)判法,建立了系統(tǒng)性能評(píng)價(jià)模型,確定了組合導(dǎo)航系統(tǒng)的網(wǎng)絡(luò)模型結(jié)構(gòu),無量綱化處理了樣本數(shù)據(jù),通過仿真實(shí)驗(yàn)表明該方法簡(jiǎn)單,易于操作,克服了評(píng)估過程中容易出現(xiàn)的模糊性和不確定性,并與基于熵的模糊綜合評(píng)判法的評(píng)估結(jié)果進(jìn)行了比較,驗(yàn)證了該模型是合理、可信的。最后,針對(duì)BP神經(jīng)網(wǎng)絡(luò)評(píng)估方法需要大樣本、計(jì)算量大等局限性,運(yùn)用了基于灰色理論的綜合評(píng)價(jià)方法,分別建立了灰色關(guān)聯(lián)度法、灰白化權(quán)和模糊數(shù)學(xué)法、灰色聚類法的評(píng)估模型,通過仿真實(shí)驗(yàn)表明了所提出的三種方法是正確合理的,都可以準(zhǔn)確的評(píng)判出組合導(dǎo)航系統(tǒng)的優(yōu)劣,而灰色聚類綜合評(píng)估法解決了灰色關(guān)聯(lián)度綜合評(píng)估法不能確定系統(tǒng)評(píng)判等級(jí)的問題,彌補(bǔ)了灰白化權(quán)和模糊數(shù)學(xué)綜合評(píng)估法客觀性差及確定的評(píng)判等級(jí)可區(qū)分度不強(qiáng)等缺點(diǎn),提高了組合導(dǎo)航系統(tǒng)性能評(píng)估的客觀性和有效性。
[Abstract]:With the development of microelectronic technology, navigation technology and control theory, the integrated navigation system, which is small in size, low in cost, low in power consumption, high in function, high in precision and high in reliability, has become a new development trend, and has been widely used in military and aviation. Space, navigation, transportation, etc. The main task of integrated navigation system is to provide accurate and reliable position, speed and attitude information for the vehicle. With the increasing degree of automation, the structure of the system is becoming more and more complex, and the relationship between the equipment in the system is becoming more and more close. The performance of the system is directly related to the safety of the carrier and all personnel. Therefore, it is of great significance to evaluate the performance of the system and lay a foundation for the optimal design of the integrated navigation system. Firstly, taking integrated navigation system as an example, this paper introduces the background and significance of the research, summarizes the development status of navigation system and its evaluation theory, based on reading a large number of related documents. This paper expounds the problems needing attention in the process of system evaluation and several common system evaluation methods, discusses the working principle of the integrated navigation system, analyzes the system performance index, and establishes the performance evaluation index system of the integrated navigation system. The method of determining the index weight is given, and the index weight is determined by the analytic hierarchy process (AHP). Secondly, aiming at the problems such as poor objectivity of index weight obtained by analytic hierarchy process (AHP), and weak degree of judgment grade determined by fuzzy comprehensive evaluation method, the system performance evaluation model is established by using fuzzy comprehensive evaluation method based on entropy. In this method, the index weight is modified by entropy weight method, and the weighted average operator is selected for fuzzy operation. According to the index weight, the comprehensive performance of the system is reflected by each index. Interval quantization is used to enhance the discriminability of the system in the same judgment level. The simulation results show that the proposed method can evaluate the performance of the system accurately and objectively, and it is compared with the fuzzy analytic hierarchy process (FAHP). Then, aiming at the nonlinearity and complexity of the performance evaluation of integrated navigation system, BP neural network has strong adaptability to nonlinear system. The comprehensive evaluation method based on BP neural network is used to establish the system performance evaluation model. The network model structure of the integrated navigation system is determined and the dimensionless sample data is processed. The simulation results show that the method is simple and easy to operate and overcomes the fuzziness and uncertainty in the evaluation process. Compared with the fuzzy comprehensive evaluation method based on entropy, it is proved that the model is reasonable and reliable. Finally, aiming at the limitation of BP neural network evaluation method, such as large sample and large amount of calculation, the comprehensive evaluation method based on grey theory is used, and the grey correlation degree method, gray whitening weight method and fuzzy mathematics method are established, respectively. The evaluation model of grey clustering method is proved to be correct and reasonable by simulation experiments, and the advantages and disadvantages of integrated navigation system can be judged accurately. The grey cluster comprehensive evaluation method solves the problem that the grey relational degree comprehensive evaluation method can not determine the system evaluation grade, and makes up for the shortcomings of the grey and white weight and fuzzy mathematics comprehensive evaluation method, such as the objectivity of the evaluation method and the degree of discrimination can not be strong, and so on. The objectivity and effectiveness of integrated navigation system performance evaluation are improved.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN967.2

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 白亮;;基于熵權(quán)模糊綜合評(píng)判法的情報(bào)融合性能評(píng)估[J];艦船電子工程;2013年04期

2 張樂;李武周;巨養(yǎng)鋒;張紅林;;基于圓概率誤差的定位精度評(píng)定辦法[J];指揮控制與仿真;2013年01期

3 王有成;敖志剛;胡波;張康益;唐長(zhǎng)春;;基于BP網(wǎng)絡(luò)的武器裝備運(yùn)用合理性評(píng)估[J];計(jì)算機(jī)與數(shù)字工程;2013年01期

4 石德方;余選召;張曉東;;基于BP神經(jīng)網(wǎng)絡(luò)的用頻效能評(píng)估研究[J];科技信息;2013年02期

5 趙欣;王躍鋼;王仕成;張金生;楊述華;;一種組合導(dǎo)航信息融合算法品質(zhì)評(píng)估方法[J];中國(guó)慣性技術(shù)學(xué)報(bào);2012年02期

6 雷鳴;楚威;李陽(yáng);;基于BP神經(jīng)網(wǎng)絡(luò)的系統(tǒng)綜合效能評(píng)估方法[J];指揮信息系統(tǒng)與技術(shù);2012年01期

7 吳笛;;基于BP神經(jīng)網(wǎng)絡(luò)的航天發(fā)射平臺(tái)性能評(píng)估研究[J];機(jī)床與液壓;2011年17期

8 孫淑光;;多傳感器組合導(dǎo)航系統(tǒng)性能評(píng)估[J];計(jì)算機(jī)工程;2011年03期

9 李元鋒;李正生;王洋;;基于模糊綜合評(píng)判的多指標(biāo)匹配算法性能評(píng)估[J];光電工程;2010年08期

10 陳希祥;邱靜;劉冠軍;;基于層次分析法與模糊綜合評(píng)判的測(cè)試設(shè)備選擇方法研究[J];兵工學(xué)報(bào);2010年01期

相關(guān)博士學(xué)位論文 前3條

1 盧鴻謙;SINS/GPS組合導(dǎo)航性能增強(qiáng)技術(shù)研究[D];哈爾濱工業(yè)大學(xué);2006年

2 周衛(wèi)東;組合導(dǎo)航系統(tǒng)應(yīng)用軟件可靠性研究[D];哈爾濱工程大學(xué);2006年

3 錢華明;故障診斷與容錯(cuò)技術(shù)及其在組合導(dǎo)航系統(tǒng)中的應(yīng)用研究[D];哈爾濱工程大學(xué);2004年

相關(guān)碩士學(xué)位論文 前10條

1 付強(qiáng);車載組合導(dǎo)航系統(tǒng)魯棒H_∞濾波[D];沈陽(yáng)工業(yè)大學(xué);2011年

2 王沖;組合導(dǎo)航系統(tǒng)故障診斷方法集成與系統(tǒng)設(shè)計(jì)[D];哈爾濱工程大學(xué);2011年

3 于國(guó)龍;嵌入式操作系統(tǒng)的實(shí)時(shí)性分析與研究[D];蘭州理工大學(xué);2010年

4 馮遠(yuǎn)遠(yuǎn);IRS/GNSS導(dǎo)航綜合性能評(píng)估技術(shù)[D];南京航空航天大學(xué);2010年

5 楊俊峰;灰色系統(tǒng)理論在軟件可信性評(píng)估中的應(yīng)用研究[D];貴州大學(xué);2009年

6 費(fèi)智聰;熵權(quán)—層次分析法與灰色—層次分析法研究[D];天津大學(xué);2009年

7 王哲;組合導(dǎo)航系統(tǒng)性能測(cè)試平臺(tái)的改進(jìn)研發(fā)[D];上海交通大學(xué);2008年

8 倪靜靜;INS/GPS組合導(dǎo)航系統(tǒng)性能評(píng)估平臺(tái)的開發(fā)[D];上海交通大學(xué);2007年

9 楊睿;多傳感器融合導(dǎo)航系統(tǒng)的數(shù)據(jù)處理及性能分析[D];南京航空航天大學(xué);2007年

10 邊德飛;多傳感器融合導(dǎo)航系統(tǒng)性能評(píng)估算法研究[D];南京航空航天大學(xué);2007年

，

本文編號(hào)：2396934