本文關(guān)鍵詞： 車輛定位 雙模衛(wèi)星定位系統(tǒng) 緊耦合 復(fù)雜環(huán)境 車內(nèi)總線　出處：《東南大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：目前汽車保有量爆炸式的增長(zhǎng)給人們生活帶來(lái)了便利,同時(shí)也使得交通擁堵及安全問(wèn)題日益突出。因此發(fā)達(dá)國(guó)家紛紛開(kāi)展了無(wú)人駕駛汽車、車路協(xié)同等智能交通技術(shù)的研究,意在通過(guò)智能交通技術(shù)改善交通狀況、保障車輛安全行駛。車輛導(dǎo)航定位技術(shù)是實(shí)現(xiàn)智能交通的重要前提之一。本文針對(duì)車輛在復(fù)雜環(huán)境下單模衛(wèi)星導(dǎo)航系統(tǒng)無(wú)法連續(xù)、可靠定位的問(wèn)題,研究了基于車內(nèi)總線的車輛雙模衛(wèi)星緊耦合定位技術(shù),以實(shí)現(xiàn)車輛準(zhǔn)確、連續(xù)、可靠定位。具體研究?jī)?nèi)容如下：1)構(gòu)建了基于車內(nèi)總線的多傳感器信息采集軟、硬件平臺(tái),實(shí)現(xiàn)多種傳感器信息的同步采集、存儲(chǔ)和處理；2)通過(guò)對(duì)雙模衛(wèi)星導(dǎo)航系統(tǒng)星歷及原始數(shù)據(jù)的解算,獲取偽距、衛(wèi)星位置等信息,并通過(guò)初步選星,剔除噪聲較大的信號(hào)；3)構(gòu)建了基于降維慣性系統(tǒng)的車輛定位模型,然后通過(guò)無(wú)跡卡爾曼濾波緊耦合算法融合雙模衛(wèi)星定位系統(tǒng)、輪速傳感器、降維慣性單元和電子羅盤的信息,實(shí)現(xiàn)復(fù)雜環(huán)境下車輛可靠定位；4)依據(jù)模糊算法自適應(yīng)調(diào)整觀測(cè)噪聲方差,進(jìn)一步提高復(fù)雜環(huán)境下車輛的定位精度；5)針對(duì)所提出融合定位方案,設(shè)計(jì)相應(yīng)的實(shí)車實(shí)驗(yàn)進(jìn)行論證,實(shí)驗(yàn)對(duì)比了不同濾波算法和觀測(cè)噪聲方差模糊設(shè)定的融合定位系統(tǒng)定位效果；目前本課題已經(jīng)完成上述內(nèi)容,通過(guò)實(shí)車實(shí)驗(yàn)證明,基于車內(nèi)總線的雙模衛(wèi)星融合定位算法能夠有效解決復(fù)雜環(huán)境下車輛可靠、連續(xù)、準(zhǔn)確定位的問(wèn)題,并且具有成本低、魯棒性好等優(yōu)點(diǎn)。
[Abstract]:At present, the explosive growth of car ownership has brought convenience to people's lives, at the same time, it also makes traffic congestion and safety problems more and more prominent. Therefore, developed countries have carried out research on intelligent transportation technology such as driverless cars, vehicle-road coordination and so on. The purpose of this paper is to improve the traffic conditions and ensure the safe driving of vehicles through intelligent transportation technology. The vehicle navigation and positioning technology is one of the important prerequisites for the realization of intelligent transportation. In this paper, the single mode satellite navigation system for vehicles in complex environment can not be continuous. In order to realize the accurate, continuous and reliable positioning of the vehicle, the problem of reliable positioning is studied. The software of multi-sensor information acquisition based on the in-vehicle bus is constructed. The hardware platform realizes the synchronous acquisition, storage and processing of various sensor information. By solving the ephemeris and original data of the dual-mode satellite navigation system, the pseudo-range, satellite position and other information are obtained, and the initial star selection is carried out. The vehicle positioning model based on reduced-dimension inertial system is constructed, and the information of dual-mode satellite positioning system, wheel speed sensor, reduced-dimension inertial unit and electronic compass is fused by unscented Kalman filter tight coupling algorithm. To realize reliable vehicle positioning in complex environment) according to fuzzy algorithm, adjust the variance of observation noise adaptively, and further improve the positioning accuracy of vehicle in complex environment. (5) in view of the proposed fusion positioning scheme, we design the corresponding real vehicle experiment to demonstrate it. The effect of the fusion positioning system based on different filtering algorithms and fuzzy setting of the observed noise variance is compared. The above contents have been completed in this paper, which is proved by the actual vehicle experiment. The dual-mode satellite fusion location algorithm based on in-vehicle bus can effectively solve the problem of reliable, continuous and accurate positioning of vehicles in complex environments, and has the advantages of low cost and good robustness.
【學(xué)位授予單位】：東南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：U463.67

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 劉大鵬;許勇;;CAN網(wǎng)絡(luò)的車載控制平臺(tái)設(shè)計(jì)[J];計(jì)算機(jī)測(cè)量與控制;2014年01期

2 李鶴峰;黨亞民;秘金鐘;陽(yáng)凡林;;BDS與GPS、GLONASS多模融合導(dǎo)航定位時(shí)空統(tǒng)一[J];大地測(cè)量與地球動(dòng)力學(xué);2013年04期

3 吳海玲;陳?ài)?;美國(guó)GPS應(yīng)用服務(wù)技術(shù)文件簡(jiǎn)介[J];數(shù)字通信世界;2010年12期

4 龐軍平;田夢(mèng)君;陳華;;基于串口通訊和多線程技術(shù)的應(yīng)用軟件開(kāi)發(fā)[J];機(jī)械與電子;2009年02期

5 王笑京;;智能交通系統(tǒng)研發(fā)歷程與動(dòng)態(tài)述評(píng)[J];城市交通;2008年01期

6 童亮;;基于CAN總線的車用智能傳感器系統(tǒng)設(shè)計(jì)[J];傳感器與微系統(tǒng);2008年01期

7 ;An Adaptive UKF Algorithm for the State and Parameter Estimations of a Mobile Robot[J];自動(dòng)化學(xué)報(bào);2008年01期

8 董紅政;王忠勇;史曉鵬;;基于MSComm控件實(shí)現(xiàn)串行通信的方法[J];微計(jì)算機(jī)信息;2007年27期

9 王偉,王敏;多線程技術(shù)在串口通信中的應(yīng)用及實(shí)現(xiàn)[J];計(jì)算機(jī)應(yīng)用與軟件;2004年02期

10 朱莊生,萬(wàn)德鈞,王慶;航位推算累積誤差實(shí)時(shí)修正算法研究[J];中國(guó)慣性技術(shù)學(xué)報(bào);2003年03期

，

本文編號(hào)：1542179