论文标题
通过整合低成本GPS,低成本MEMS IMU的动态态度估计改进
Dynamic Attitude Estimation Improvement for Low-cost MEMS IMU by Integrating Low-cost GPS
论文作者
论文摘要
本文提出了一个基于全球位置系统(GPS)接收器与惯性微电机械系统(MEMS)的传感器的集成,针对小型空中机器人的低成本六(6-DOF)导航系统。在与低成本GPS的惯性测量单元(IMU)的融合问题中,涉及时间同步误差对态度估计的影响。提出了一种可以估计运动状态和同时估算时间同步误差的融合算法。该算法添加了时间估计循环,以提高估计精度。与其他状态增强估计方法相比,该方法具有较低的计算负担,避免了低样本率中离散误差。估计算法是在低成本嵌入式微处理器中实现的,其中算法的更新速率可以实现超过100 Hz,因此无需高性能计算单元。在机器人实验中,提出的算法是小型空中机器人的导航解决方案。当机器人以明显的加速度移动时,测试了自设计系统的准确性和可靠性。
This paper proposes a low-cost six Degree-of-Freedom (6-DOF) navigation system for small aerial robots based on the integration of Global Position System (GPS) receiver with sensors of inertional Microelectromechanical Systems (MEMS). In the problem of fusing Inertial Measurement Unit (IMU) with low-cost GPS, the effect of time synchronization error on attitude estimation is concerned. A fusion algorithm which can estimate the motion states and the time synchronization error simultaneously is proposed. This algorithm adds a time estimation loop to improve estimation accuracy. Compared with another states augmented estimation approach, this method has the advantages of lower computation burden, avoidance of the discretization error in the low sample rate. The estimation algorithm is implemented in an low-cost embedded microprocessor where the update rate of algorithm can achieve more than 100 Hz, and therefore high-performance computational units are not necessary. In robotic experiment, the proposed algorithm serves as the navigation solution for a small aerial robot. The accuracy and reliability of the self-designed system are tested when the robot is moving with significant acceleration.