Real-time vision-inertial landing navigation for fixed-wing aircraft with CFC-CKF

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Guanfeng Yu, Lei Zhang, Siyuan Shen, Zhengjun Zhai
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Abstract

Vision-inertial navigation offers a promising solution for aircraft to estimate ego-motion accurately in environments devoid of Global Navigation Satellite System (GNSS). However, existing approaches have limited adaptability for fixed-wing aircraft with high maneuverability and insufficient visual features, problems of low accuracy and subpar real-time arise. This paper introduces a novel vision-inertial heterogeneous data fusion methodology, aiming to enhance the navigation accuracy and computational efficiency of fixed-wing aircraft landing navigation. The visual front-end of the system extracts multi-scale infrared runway features and computes geo-reference runway image as observation. The infrared runway features are recognized efficiently and robustly by a lightweight end-to-end neural network from blurry infrared images, and the geo-reference runway is generated through projection of the runway’s prior geographical information and prior pose. The fusion back-end of the navigation system is the Covariance Feedback Control based Cubature Kalman Filter (CFC-CKF) framework, which tightly integrates visual observations and inertial measurements for zero-drift pose estimation and curbs the effect of inaccurate kinematic noise statistics. Finally, real flight experiments demonstrate that the algorithm can estimate the pose at a frequency of 100 Hz and fulfill the navigation accuracy requirements for high-speed landing of fixed-wing aircraft.

Abstract Image

利用 CFC-CKF 为固定翼飞机提供实时视觉惯性着陆导航
视觉惯性导航为飞机在没有全球导航卫星系统(GNSS)的环境中准确估计自我运动提供了一种前景广阔的解决方案。然而,现有方法对于机动性强、视觉特征不足的固定翼飞机的适应性有限,存在精度低、实时性差等问题。本文介绍了一种新型视觉-惯性异构数据融合方法,旨在提高固定翼飞机着陆导航的导航精度和计算效率。该系统的视觉前端提取多尺度红外跑道特征,并计算地理参考跑道图像作为观测值。红外跑道特征由轻量级端到端神经网络从模糊的红外图像中高效、鲁棒性地识别出来,而地理参考跑道则是通过投影跑道的先验地理信息和先验姿态生成的。导航系统的融合后端是基于协方差反馈控制的立方卡尔曼滤波器(CFC-CKF)框架,它将视觉观测和惯性测量紧密结合,实现零漂移姿态估计,并抑制不准确的运动噪声统计的影响。最后,实际飞行实验证明,该算法能以 100 Hz 的频率估计姿态,满足固定翼飞机高速着陆的导航精度要求。
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来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
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