Application of vision aided strapdown integrated navigation in lane vehicles

Qi Wang, Chang-song Yang, Shaoen Wu
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Abstract

The application of global navigation satellite system (GNSS) is extensive in lane applications with the development of science and technology. Vision aided strapdown integrated navigation is an effective aided-navigation method in the case of GNSS failure in lane vehicles, which plays an important role in realising high-precision navigation of lane navigation system. A vision-aided navigation system based on GNSS positioning is constructed using the electrical powered platform as the research object. The hardware platform of vision navigation system is presented and digital image processing is used to segment the collected lane image. The image pre-processing operation, including denoising filtering and greyscale processing, is carried out to complete the segmentation and get the effective navigation area. According to the effective area of navigation, a navigation datum line is extracted by the least squares linear fitting and Hough transform. According to the camera imaging model and the camera's internal and external parameters, the navigation datum line in the image coordinates is transformed into the world coordinates, and the heading angle is calculated. Kalman filter algorithm is used to fuse the navigation parameters of the vision navigation module and the GNSS positioning module, and the integrated navigation model is established.
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视觉辅助捷联组合导航在车道车辆中的应用
随着科学技术的发展,全球卫星导航系统(GNSS)在车道上的应用越来越广泛。视觉辅助捷联组合导航是车道车辆GNSS失效情况下的一种有效辅助导航方法,对实现车道导航系统的高精度导航具有重要作用。以电动平台为研究对象,构建了基于GNSS定位的视觉辅助导航系统。提出了视觉导航系统的硬件平台,并采用数字图像处理技术对采集到的车道图像进行分割。进行图像预处理操作,包括去噪滤波和灰度处理,完成图像分割,得到有效的导航区域。根据导航有效面积,采用最小二乘线性拟合和霍夫变换提取导航基准线。根据摄像机成像模型和摄像机的内外参数,将图像坐标中的导航基准线转换为世界坐标,计算航向角。利用卡尔曼滤波算法对视觉导航模块和GNSS定位模块的导航参数进行融合,建立集成导航模型。
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