Adaptive Cooperative Navigation Strategies for Complex Environments

F. Causa, G. Fasano
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引用次数: 1

Abstract

Multi-UAV Cooperation is a promising strategy to enhance navigation performance. In this framework, a UAV, termed chief, can exploit cooperative vehicles, deemed deputies, who share positioning information and enable relative measurements by ranging and/or bearing sensors, to improve its state estimation accuracy. Different cooperative strategies are available depending on the status of the formation. Specifically, based on the GNSS coverage conditions, cooperative aiding can be used to support position and/or attitude estimation. This paper introduces an adaptive navigation filter that automatically selects the relevant strategy to be used in each phase of flight. In addition, within a multi-UAV scenario, the effect of simultaneous exploitation of different cooperative navigation strategies onboard different UAVs is investigated. The adaptive filter is tested both on simulated and experimental flight data, showing the benefit of adaptively using shared data within the cooperative multi-vehicle system.
复杂环境下的自适应协同导航策略
多无人机合作是一种很有前途的提高导航性能的策略。在这个框架中,无人机(chief)可以利用合作车辆(称为副手)共享定位信息,并通过测距和/或方位传感器进行相对测量,以提高其状态估计精度。不同的合作策略取决于编队的状态。具体来说,基于GNSS覆盖条件,协同辅助可用于支持位置和/或姿态估计。本文介绍了一种自适应导航滤波器,该滤波器在飞行的各个阶段自动选择相应的策略。此外,在多无人机场景下,研究了不同无人机同时使用不同协同导航策略的效果。在模拟和实验飞行数据上对自适应滤波器进行了测试,显示了在协作多飞行器系统中自适应使用共享数据的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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