This paper introduces a method for enabling multiple small unmanned aircraft to improve navigational accuracy in Global Positioning System (GPS)-denied environments by cooperatively sharing information. The method uses a multilevel framework called relative navigation and visual-inertial odometry: both of which have been used for single-vehicle GPS-denied navigation. This work modifies the relative navigation architecture by adding the necessary elements to enable decentralized, cooperative operations. The proposed framework also includes the ability to incorporate intervehicle measurements and uses a new concept called the coordinated reset, which is necessary for optimizing the cooperative odometry and improving localization. A simple communication protocol is presented, as well as flight-test results that show its effectiveness. The method is first demonstrated in simulation, including Monte Carlo testing, to show the expected improvement gained from cooperation. Finally, results from hardware testing are presented that show the ability of the system to reject initialization errors, to operate with temporary communications dropouts, and to greatly reduce the total amount of shared data compared to a naive approach. The proposed method is able to improve both global navigation accuracy and the accuracy of the relative aircraft positions for missions that require formation flying.

本文介绍了一种通过协作共享信息，使多架小型无人机能够在全球定位系统（GPS）受限的环境中提高导航精度的方法。该方法使用了称为相对导航和视觉惯性里程表的多级框架：这两种方法都已用于单车GPS拒绝导航。这项工作通过添加必要的元素以实现分散的协作操作来修改相对导航体系结构。所提出的框架还具有合并车辆测量的能力，并使用了称为协调重置的新概念，这对于优化协作里程计和改善定位是必不可少的。提出了一个简单的通信协议，以及表明其有效性的飞行测试结果。该方法首先在包括蒙特卡洛测试在内的仿真中得到证明，以显示合作带来的预期改进。最后，从硬件测试得出的结果表明，与单纯的方法相比，该系统具有拒绝初始化错误，具有临时通信中断的能力以及极大地减少共享数据总量的能力。所提出的方法能够提高全球导航精度以及需要编队飞行的任务的相对飞机位置的精度。与幼稚的方法相比，可以大大减少共享数据的总量。所提出的方法能够提高全球导航精度和需要编队飞行的任务的相对飞机位置的精度。与幼稚的方法相比，可以大大减少共享数据的总量。所提出的方法能够提高全球导航精度以及需要编队飞行的任务的相对飞机位置的精度。