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Research on Low-Cost Attitude Estimation for MINS/Dual-Antenna GNSS Integrated Navigation Method

机译:MINS /双天线GNSS组合导航方法的低成本姿态估计研究

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摘要

A high-precision navigation system is required for an unmanned vehicle, and the high-precision sensor is expensive. A low-cost, high-precision, dual-antenna Global Navigation Satellite System/Micro-electromechanical Systems-Inertial Navigation System (GNSS/MINS) combination method is proposed. The GNSS with dual antennas provides velocity, position, and attitude angle information as the measurement information is combined with the MINS. By increasing the heading angle, pitch angle, velocity, the accuracy of the integrated system is improved. The Extended Kalman Filtering (EKF) integrated algorithm simulation is designed to verify the feasibility and is realized based on the Field Programmable Gate Array and Advanced RISC Machine (ARM+FPGA) system. Static and dynamic tests were performed using the Synchronous Position, Attitude and Navigation (SPAN-CPT) as a reference system. The results show that the velocity, position, and attitude angle accuracy were improved. The yaw angle and pitch angle accuracy were 0.2° Root Mean Square (RMS) and 0.3° RMS, respectively. The method can be used as a navigation system for the unmanned vehicle.
机译:无人驾驶车辆需要高精度的导航系统,并且高精度传感器很昂贵。提出了一种低成本,高精度,双天线的全球导航卫星系统/微机电系统-惯性导航系统(GNSS / MINS)组合方法。当测量信息与MINS结合在一起时,带有双天线的GNSS可提供速度,位置和姿态角信息。通过增加航向角,俯仰角,速度,可以提高集成系统的精度。扩展卡尔曼滤波(EKF)集成算法仿真旨在验证可行性,并基于现场可编程门阵列和高级RISC机器(ARM + FPGA)系统实现。使用同步位置,姿态和导航(SPAN-CPT)作为参考系统进行了静态和动态测试。结果表明,速度,位置和姿态角精度均得到改善。偏航角精度和俯仰角精度分别为0.2°均方根(RMS)和0.3°RMS。该方法可用作无人驾驶车辆的导航系统。

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