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INS/GPS Based State Estimation of Micro Air Vehicles Using Inertial Sensors

机译:基于惯性传感器的基于INS / GPS的微型飞行器状态估计

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摘要

The most attractive and attention seeking topic of aerospace world is Micro Air Vehicle (MAV) which broadly speaking it can be categorized as significantly smaller aircraft than conventional aircrafts. Micro Air Vehicles can be divided as autonomous, semi-autonomous and remote controlled flying machines which can be fixed wing MAV, Flapping wing MAV and rotary wing MAV. One of the crucial problems regarding Micro Air Vehicle is its stability which is basically concerned with the guidance, navigation and control. State Estimation is an important aspect of navigation and this paper deals with the state estimation problem of micro Air vehicle. Inertial sensors are being used including MEMS Gyro, MEMS Accelerometer, Magnetometer and GPS in Inertial Measurement Unit (IMU) and three Discrete Time Extended Kalman Filter Schemes have been used for the state estimation purpose. Trajectory and required data is recorded in Flight Simulator and MATLAB has been used for the simulations. A comprehensive parametric study is carried out and results are analyzed and briefly discussed.
机译:航空航天界最吸引人和关注的话题是微型飞行器(MAV),从广义上讲,它可以归类为比传统飞机小得多的飞机。微型飞行器可以分为自动,半自动和遥控飞行器,它们可以是固定翼MAV,襟翼翼MAV和旋转翼MAV。关于微型飞行器的关键问题之一是其稳定性,其基本上与制导,导航和控制有关。状态估计是导航的重要方面,本文研究了微型飞行器的状态估计问题。使用惯性传感器,包括惯性测量单元(IMU)中的MEMS陀螺仪,MEMS加速度计,磁力仪和GPS,并且三个离散时间扩展卡尔曼滤波方案已用于状态估计。轨迹和所需数据记录在Flight Simulator中,并且MATLAB已用于仿真。进行了全面的参数研究,并对结果进行了分析和简要讨论。

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