Improvement of the standard GNSS/IMU solution for UAVs using already existing redundant navigation sensors

M. Dorn, R. Lesjak, M. Wieser
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引用次数: 10

Abstract

Navigation parameters like position, velocity, and attitude are essential for many UAV (Unmanned Aerial Vehicle) applications. Especially for automatic or autonomous UAV applications, the navigation parameters have to be very accurate and reliable. Currently, the reliability of all critical system components (like the communication or the navigation module) is improved by the redundancy concept. Therefore, the navigation module consists of at least two GNSS (Global Navigation Satellite System) antennas and receivers and two IMUs (Inertial Measurement Units). But these redundant sensors work completely in a separate way, so the redundancy is used only as backup in the case of sensor failures. This paper deals with the improvement of the accuracy and reliability of all navigation parameters by using the already existing redundant navigation sensors. A loosely-coupled extended Kalman filter integrates the positions of the two GNSS antennas with IMU and magnetometer measurements. Additionally, precise data (Precise Point Positioning) is added to improve the accuracy of the navigation solution, and the moving baseline between the redundant GNSS antennas is added to support the heading. This paper shows the total potential for the navigation solution by exploiting the already existing redundant navigation sensors.
使用现有冗余导航传感器改进无人机的标准GNSS/IMU解决方案
导航参数如位置、速度和姿态对许多无人机(UAV)应用至关重要。特别是对于自动或自主无人机应用,导航参数必须非常准确和可靠。目前,所有关键系统组件(如通信或导航模块)的可靠性都是通过冗余的概念来提高的。因此,导航模块至少由两个GNSS(全球导航卫星系统)天线和接收器以及两个imu(惯性测量单元)组成。但这些冗余传感器完全以独立的方式工作,因此冗余仅在传感器故障的情况下用作备份。本文研究了利用现有的冗余导航传感器来提高各导航参数的精度和可靠性。一个松散耦合的扩展卡尔曼滤波器将两个GNSS天线的位置与IMU和磁力计测量相结合。此外,还增加了精确数据(精确点定位)以提高导航解决方案的精度,并增加了冗余GNSS天线之间的移动基线以支持航向。本文展示了利用现有冗余导航传感器的导航解决方案的总潜力。
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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