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Development of High-precision Navigation Algorithm by Fusion of GPS and MEMS Sensors

机译：通过GPS和MEMS传感器融合开发高精度导航算法

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This paper presents development of highly accuratenavigation algorithm by sensor fusion, integratinginformation of civil-use GPS receiver and several MEMSsensors. It intends to make up navigation equipmentgenerally used for small moving objects such as robots andUnmanned Aerial Vehicle (UAV). Then it is necessary touse small, light but low-accuracy MEMS sensors asmeasurement devices for achieving the goal, and thereforethis research provides algorithm to integrate themeffectively and constructs more accurate, highly-robust andreliable navigation system than previous researches byutilizing many kinds of MEMS sensors and the INS/GPSintegrated navigation system. A civil-use GPS receiver,two different-range tri-axis gyroscopes and accelerometers,a tri-axis magnetic sensor and a pressure sensor aremounted on the navigation equipment, and informationobtained by all of them is integrated by extended Kalmanfilter. As for combining different-range sensors, it ispossible not only to enlarge measurement range simply, butalso to improve quality of the signals by focusing on theirfrequency responses and filtering methods. This paperintroduces the innovative way to treat these multiplesensors. Also, refined methods of integrating a magneticsensor and a pressure sensor into the navigation system aredescribed. In the latter, functionality of the algorithm isvalidated with computational simulations with aircraftnavigation data actually obtained in flight experiments.Results of the simulations show that the magnetic sensorenhances accuracy and reliability of attitude estimationespecially in the situation that the motion of an aircraft is so little that attitude estimation error can be accumulatedwithout a magnetic sensor. They also show that thepressure sensor is effective for the overall system toacquire robustness of estimating altitude and verticalvelocity especially in the situation that GPS signals are notavailable.
机译：本文介绍了高精度的发展 传感器融合，融合的导航算法 GPS接收器和几种MEMS的信息 传感器。它打算组成导航设备 通常用于小型移动物体，例如机器人和 无人机（UAV）。然后有必要 使用小型，轻便但低精度的MEMS传感器作为 用于实现目标的测量设备，因此 这项研究提供了将它们集成的算法 有效地构建更准确，更健壮和 可靠的导航系统比以前的研究 利用多种MEMS传感器和INS / GPS 集成导航系统。一款民用GPS接收器， 两个不同范围的三轴陀螺仪和加速度计， 三轴磁传感器和压力传感器是 安装在导航设备上的信息 他们所有的人都得到了扩展卡尔曼的整合 筛选。至于组合不同距离的传感器，它是 不仅可以简单地扩大测量范围，而且 还可以通过专注于信号质量来提高信号质量 频率响应和滤波方法。这篇报告 介绍治疗这些多种疾病的创新方法 传感器。另外，整合磁的精致方法 传感器和压力传感器进入导航系统 描述。在后者中，算法的功能是 通过飞机的计算仿真进行了验证 在飞行实验中实际获得的导航数据。 仿真结果表明，磁传感器 提高姿态估计的准确性和可靠性 特别是在飞机的运动太少以至于可以累积姿态估计误差的情况下 没有磁性传感器。他们还表明 压力传感器对整个系统有效 获得估计高度和垂直方向的稳健性 速度，尤其是在没有GPS信号的情况下 可用的。

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