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

机译:GPS和MEMS传感器融合高精度导航算法的开发

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This paper presents development of highly accurate navigation algorithm by sensor fusion, integrating information of civil-use GPS receiver and several MEMS sensors. It intends to make up navigation equipment generally used for small moving objects such as robots and Unmanned Aerial Vehicle (UAV). Then it is necessary to use small, light but low-accuracy MEMS sensors as measurement devices for achieving the goal, and therefore this research provides algorithm to integrate them effectively and constructs more accurate, highly-robust and reliable navigation system than previous researches by utilizing many kinds of MEMS sensors and the INS/GPS integrated navigation system. A civil-use GPS receiver, two different-range tri-axis gyroscopes and accelerometers, a tri-axis magnetic sensor and a pressure sensor are mounted on the navigation equipment, and information obtained by all of them is integrated by extended Kalman filter. As for combining different-range sensors, it is possible not only to enlarge measurement range simply, but also to improve quality of the signals by focusing on their frequency responses and filtering methods. This paper introduces the innovative way to treat these multiple sensors. Also, refined methods of integrating a magnetic sensor and a pressure sensor into the navigation system are described. In the latter, functionality of the algorithm is validated with computational simulations with aircraft navigation data actually obtained in flight experiments. Results of the simulations show that the magnetic sensor enhances accuracy and reliability of attitude estimation especially in the situation that the motion of an aircraft is so little that attitude estimation error can be accumulated without a magnetic sensor. They also show that the pressure sensor is effective for the overall system to acquire robustness of estimating altitude and vertical velocity especially in the situation that GPS signals are not available.
机译:本文介绍了传感器融合的高精度导航算法的开发,集成了民用GPS接收器和几个MEMS传感器的信息。它打算构成一般用于小型移动物体的导航设备,如机器人和无人驾驶飞行器(UAV)。那么有必要使用小,轻,但低精度MEMS传感器作为测量装置实现的目标,因此,这项研究提供算法给他们有效地整合和结构更精确,高鲁棒性和可靠的导航系统比利用以往的研究多种MEMS传感器和INS / GPS集成导航系统。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安装在导航设备上,并且通过扩展卡尔曼滤波器集成了所有这些信息。对于组合不同范围的传感器,不仅可以简单地放大测量范围,而且还可以通过专注于它们的频率响应和过滤方法来提高信号的质量。本文介绍了对待这些多个传感器的创新方法。此外,描述了将磁传感器和压力传感器集成到导航系统中的精制方法。在后者中,算法的功能通过实际在飞行实验中实际获得的飞机导航数据进行验证。模拟结果表明,磁传感器提高了姿态估计的准确性和可靠性,特别是在飞机的运动很少的情况下,没有磁传感器可以累积姿态估计误差。他们还表明,压力传感器对整个系统有效地获得估算高度和垂直速度的稳健性,特别是在GPS信号不可用的情况下。

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