首页> 外文会议>Conference on Enhanced and Synthetic Vision 2001 Apr 16-17, 2001, Orlando, USA >Navigation Integrity Monitoring and Obstacle Detection for Enhanced Vision Systems
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Navigation Integrity Monitoring and Obstacle Detection for Enhanced Vision Systems

机译:增强视觉系统的导航完整性监控和障碍物检测

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Typically, Enhanced Vision (EV) systems consist of two main parts, sensor vision and synthetic vision. Synthetic vision usually generates a virtual out-the-window view using databases and accurate navigation data, e. g. provided by differential GPS (DGPS). The reliability of the synthetic vision highly depends on both, the accuracy of the used database and the integrity of the navigation data. But especially in GPS based systems, the integrity of the navigation can't be guaranteed. Furthermore, only objects that are stored in the database can be displayed to the pilot. Consequently, unexpected obstacles are invisible and this might cause severe problems. Therefore, additional information has to be extracted from sensor data to overcome these problems. In particular, the sensor data analysis has to identify obstacles and has to monitor the integrity of databases and navigation. Furthermore, if a lack of integrity arises, navigation data, e. g. the relative position of runway and aircraft, has to be extracted directly from the sensor data. The main contribution of this paper is about the realization of these three sensor data analysis tasks within our EY system, which uses the HiVision 35 GHz MMW radar of EADS, Ulm as the primary EV sensor. For the integrity monitoring, objects extracted from radar images are registered with both database objects and objects (e. g. other aircrafts) transmitted via data link. This results in a classification into known and unknown radar image objects and consequently, in a validation of the integrity of database and navigation. Furthermore, special runway structures are searched for in the radar image where they should appear. The outcome of this runway check contributes to the integrity analysis, too. Concurrent to this investigation a radar image based navigation is performed without using neither precision navigation nor detailed database information to determine the aircraft's position relative to the runway. The performance of our approach is demonstrated with real data acquired during extensive flight tests to several airports in Northern Germany.
机译:通常,增强视觉(EV)系统由两个主要部分组成,即传感器视觉和合成视觉。合成视觉通常使用数据库和准确的导航数据(例如)生成虚拟的窗口视图。 G。由差分GPS(DGPS)提供。合成视觉的可靠性在很大程度上取决于所用数据库的准确性和导航数据的完整性。但是尤其是在基于GPS的系统中,无法保证导航的完整性。此外,只能将存储在数据库中的对象显示给飞行员。因此,意外的障碍是看不见的,这可能会导致严重的问题。因此,必须从传感器数据中提取其他信息以克服这些问题。特别是,传感器数据分析必须识别障碍,并且必须监视数据库和导航的完整性。此外,如果出现缺乏完整性的情况,则导航数据例如。 G。跑道和飞机的相对位置必须直接从传感器数据中提取。本文的主要贡献是在我们的EY系统中实现了这三个传感器数据分析任务,该系统使用EADS的HiVision 35 GHz MMW雷达(Ulm)作为主要的EV传感器。为了完整性监视,将从雷达图像提取的对象与数据库对象和经由数据链路发送的对象(例如,其他飞机)都注册。这导致对已知和未知雷达图像对象的分类,从而对数据库和导航的完整性进行验证。此外,在雷达图像中搜索应该出现的特殊跑道结构。跑道检查的结果也有助于完整性分析。与此调查同时进行的是基于雷达图像的导航,而无需使用精确导航或详细的数据库信息来确定飞机相对于跑道的位置。在对德国北部几个机场进行的广泛飞行测试中获得的真实数据证明了我们方法的有效性。

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