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Vision aided INS for UAV auto landing navigation using SR-UKF based on two-view homography

机译:视觉辅助INS用于基于两视图单应性的SR-UKF进行无人机自动着陆导航

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An SR-UKF model for integrating INS and Vision navigation system was built to estimate the INS system error, in which regarding the INS system error equation as process model, and homography between two-view as measure model. Aiming at the invalidity of traditional homography between two views when coplanar points exactly in the word coordinate system plane, a novel expression of homography was proposed under the certain circumstances like UAV auto landing based on vision technology. To improve the efficiency and stability of filter, SR-UKF was used for states estimating, and the navigation data was compensated by the estimated result. Simulations show that the method proposed was effective to improve the accuracy of navigation system.
机译:建立了一个用于集成INS和视觉导航系统的SR-UKF模型,以估算INS系统错误,其中关于INS系统错误方程作为过程模型,以及双视图之间的定位作为测量模型。瞄准在两个视图之间的传统识别之间的无效何时在单词坐标系平面中的共同坐标系平面时,在基于视觉技术的无人机自动登陆等某些情况下提出了一种新颖的同情。为了提高滤波器的效率和稳定性,使用SR-UKF用于各种估计,导航数据通过估计结果得到补偿。模拟表明,提出的方法有效提高导航系统的准确性。

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