基于IMU的象限转子导航系统与卡尔曼滤镜

Lasmadi Lasmadi
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引用次数: 1

摘要

四旋翼飞行器在自主飞行时,导航系统对保持飞行器的稳定性和确定自身位置具有重要意义。GPS可以提供位置测量,但在特定环境下存在局限性,无法提供方位信息。本研究旨在利用状态空间模型设计基于卡尔曼滤波IMU传感器的四旋翼飞行器导航系统。利用Matlab软件建立了系统模型。卡尔曼滤波用于估计导航数据,消除传感器上的噪声,从而提高测量精度。实验结果表明,该系统模型能够提供四旋翼飞行器的方向估计和动距估计,而卡尔曼滤波模型能够有效地降低传感器原始数据的噪声。在室内测试时,该系统可提供90%以上的测量精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sistem Navigasi Quadrotor Berbasis IMU dengan Kalman Filter
The navigation system on quadrotor is important to maintain stability and determine its own position when flying autonomously. The GPS can provide the position measurement, but it has limitations in the specific environments and cannot provide the orientation information. This study aims to design the navigation system for quadrotor based on IMU sensor with Kalman filters using the state space model. The system model was developed using Matlab software. Kalman filter is designed to estimate the navigation data and eliminate noise on the sensor so that it can improve the measurement accuracy. The test results showed that the system model can provide orientation estimation and translation estimation of the quadrotor, while the Kalman filter model is acceptable to reduce noise on the sensor's raw data. When tested indoors, the system can provide the measurement accuracy above 90%.
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