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Modelling and Testing of Terrain Aided Inertial Navigation Algorithms for Land Vehicles

机译:地球车辆地形辅助惯性导航算法的建模与测试

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Sensing the terrain and using it for aiding the inertial navigation system has been widely used in air platforms since the 1960's. TERCOM and SITAN are well-known algorithms for sensing the terrain with a radar altimeter and calculating a correction for the navigation states according to a digital elevation map. In the absence of GPS signals, it is extremely important to be able to make positional fixes. In this paper, first we developed a simulation environment for a conceptual application of TAN (Terrain Aided Navigation) for land vehicles. Basically, the test platform is always on the ground so we can assume a trivial zero terrain clearance measurement and apply well-known TAN algorithms. With this new idea, an inertial measurement unit (IMU), a digital elevation map and a barometer are sufficient to apply the TAN algorithms in land vehicles. A widely used navigation aid in land navigation, odometer, is also considered in this TAN application. Error models are developed for each sensor and a dynamic model is used to simulate the IMU data of a land vehicle which moves on the terrain surface. A Kalman filter is designed to track navigation states and as a reference, truth model data is used to find the error statistics of the navigation states via Monte Carlo simulations. We also compare the simulation results with real time road test results. This paper finally discusses the requirements on the accuracy of sensors, digital maps and the vehicle capability. The vehicle has to be able to move on a land that has characteristic features for a successful application of the TAN algorithms.
机译:自1960年代以来,对地形传感并使用它来说,以帮助其辅助惯性导航系统已被广泛应用于空中平台。 TERCOM和SITAN是众所周知的算法,用于用雷达高度计感测地形,并根据数字高度地图计算导航状态的校正。在没有GPS信号的情况下,能够制造位置修复是非常重要的。在本文中,首先,我们开发了一种用于陆路(地形辅助导航)的概念应用的仿真环境。基本上,测试平台始终在地面上,因此我们可以假设一个微不足道的零地形清除测量并应用众所周知的TAN算法。利用这个新想法,惯性测量单元(IMU),数字高度图和气压计足以在陆车辆中应用TAN算法。在该TAN应用中也考虑了陆地航行,里程表中广泛使用的导航援助。为每个传感器开发错误模型,并且动态模型用于模拟在地形表面上移动的陆地车辆的IMU数据。 Kalman滤波器旨在跟踪导航状态,作为参考,真理模型数据用于通过Monte Carlo仿真查找导航状态的错误统计信息。我们还将模拟结果与实时道路测试结果进行比较。本文最终探讨了对传感器,数字地图和车辆能力的准确性的要求。车辆必须能够在具有成功应用TAN算法的地上移动具有特征特征的地面。

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