Relative navigation of fixed‐wing aircraft in GPS‐denied environments

Relative navigation of fixed‐wing aircraft in GPS‐denied environments
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GPS 失效环境中固定翼飞机的相对导航

DOI:
10.1002/navi.364
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发表时间:
2020
期刊:
NAVIGATION
影响因子:
--
通讯作者:
McLain, Tim
McLain, Tim
中科院分区:
--
文献类型:
--
作者:
Ellingson, Gary;Brink, Kevin;McLain, Tim

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这项工作通过考虑固定翼特定的传感要求并使用称为相对导航的方法作为总体框架,使固定翼UAS上的GPS拒绝飞行成为可能。发展的里程计,前端,EKF为基础的估计,只利用一个单目相机和惯性测量单元(IMU)。该滤波器采用多状态约束卡尔曼滤波器的测量模型。过滤器还定期重置其原点,以配合关键帧图像的声明。关键帧到关键帧的里程估计及其协方差被发送到将全局状态表示为姿势图的全局后端。后端更适合于表示非线性不确定性,并纳入机会主义的全局约束。我们还介绍了一种方法来占前端速度偏差在后端优化。本文提供了前端估计器的仿真和硬件飞行测试结果,并对前端数据进行了几次后端优化。
This work enables GPS-denied flight on fixed-wing UAS by accounting for fixed-wing-specific sensing requirements and using a methodology called relative navigation as an overarching framework. The development of an odometry-like, front-end, EKF-based estimator that utilizes only a monocular camera and an inertial measurement unit (IMU) is presented. The filter uses the measurement model of the multi-state-constraint Kalman filter. The filter also regularly resets its origin in coordination with the declaration of keyframe images. The keyframe-to-keyframe odometry estimates and their covariances are sent to a global back end that represents the global state as a pose graph. The back end is better suited to represent nonlinear uncertainties and incorporate opportunistic global constraints. We also introduce a method to account for front-end velocity bias in the back-end optimization. The paper provides simulation and hardware flight-test results of the front-end estimator and performs several back-end optimizations on the front-end data.
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发表时间: 2020-06-23
影响因子: 9.2
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