基于车内总线的车辆双模卫星融合定位技术研究

发布时间：2018-02-27 09:51

本文关键词： 车辆定位双模卫星定位系统紧耦合复杂环境车内总线　出处：《东南大学》2016年硕士论文　论文类型：学位论文

【摘要】：目前汽车保有量爆炸式的增长给人们生活带来了便利,同时也使得交通拥堵及安全问题日益突出。因此发达国家纷纷开展了无人驾驶汽车、车路协同等智能交通技术的研究,意在通过智能交通技术改善交通状况、保障车辆安全行驶。车辆导航定位技术是实现智能交通的重要前提之一。本文针对车辆在复杂环境下单模卫星导航系统无法连续、可靠定位的问题,研究了基于车内总线的车辆双模卫星紧耦合定位技术,以实现车辆准确、连续、可靠定位。具体研究内容如下：1)构建了基于车内总线的多传感器信息采集软、硬件平台,实现多种传感器信息的同步采集、存储和处理；2)通过对双模卫星导航系统星历及原始数据的解算,获取伪距、卫星位置等信息,并通过初步选星,剔除噪声较大的信号；3)构建了基于降维惯性系统的车辆定位模型,然后通过无迹卡尔曼滤波紧耦合算法融合双模卫星定位系统、轮速传感器、降维惯性单元和电子罗盘的信息,实现复杂环境下车辆可靠定位；4)依据模糊算法自适应调整观测噪声方差,进一步提高复杂环境下车辆的定位精度；5)针对所提出融合定位方案,设计相应的实车实验进行论证,实验对比了不同滤波算法和观测噪声方差模糊设定的融合定位系统定位效果；目前本课题已经完成上述内容,通过实车实验证明,基于车内总线的双模卫星融合定位算法能够有效解决复杂环境下车辆可靠、连续、准确定位的问题,并且具有成本低、鲁棒性好等优点。
[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.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U463.67

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