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.

中文翻译：

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GPS拒绝环境中固定翼飞机的相对导航

这项工作通过考虑固定翼特定的感测要求，并使用称为相对导航的方法作为总体框架，可以在固定翼UAS上进行GPS拒绝飞行。介绍了仅使用单眼相机和惯性测量单元（IMU）的基于里程表的前端，基于EKF的估算器的开发。该滤波器使用多状态约束卡尔曼滤波器的测量模型。过滤器还会与关键帧图像的声明一起定期重置其来源。关键帧到关键帧的里程计估计及其协方差被发送到以姿态图表示全局状态的全局后端。后端更适合于表示非线性不确定性并结合机会全局约束。我们还介绍了一种在后端优化中解决前端速度偏差的方法。本文提供了前端估计器的仿真和硬件飞行测试结果，并对前端数据执行了多个后端优化。