基于两位置法与改进STEKF的农机航向角测量方法

Method for Measuring Heading Angle of Agricultural Machinery Based on Two-position Method and Improved STEKF

摘要:

针对单天线GNSS农机导航系统起步和低速时航向测量不准问题，本文基于两位置法与改进强跟踪扩展卡尔曼滤波算法（Strong tracking extended Kalman filter，STEKF）进行农机航向测量技术研究，设计一种适用于单天线GNSS/IMU融合的农机航向测量方法。采用两位置法测量高速作业农机航向，基于IMU输出的9轴数据和GNSS输出的位置与速度信息，提出改进强跟踪自适应矩阵R STEKF算法对农机低速行驶时的航向准确测量，设计了基于两位置法与改进STEKF航向的一维卡尔曼滤波融合方法。以雷沃M-1204型拖拉机为试验平台，进行了速度梯度变化工况下农机航向测量精度和稳定性验证试验，结果表明，在农机从静止状态起步，经历包含直线和曲线的混合路段，在速度0.36~5.40km/h过程中，本文提出的融合航向测量方法获取的航向角与双天线GNSS获取的航向角误差不超过0.50°，表明本文方法适用于农机静止起步到低速运动状态下农机航向稳定获取，提高了单天线农机导航起步和低速驾驶控制精度和稳定性，可为高精度农机自主无人作业提供技术基础。

Abstract:

To solve the problems of low accuracy in heading measurement for single-antenna GNSS agricultural machinery navigation system at low speed and the difficulty of starting up, research on agricultural machinery heading measurement technology was conducted based on two-position method and improved STEKF. A suitable heading measurement method for GNSS/IMU fusion in single-antenna agricultural machinery was designed. The heading of high-speed agricultural machinery was measured by the two-position method, and the heading of low-speed agricultural machinery was measured by the improved STEKF algorithm based on the 9-axis data output by the IMU and the position and speed information output by the GNSS. A one-dimensional Kalman filter fusion method based on the two-position method and the improved STEKF heading was designed. The M-1204 tractor produced by Lovol was used as the experimental platform to verify the heading measurement accuracy and stability under speed gradient change conditions. The results showed that during the process of starting up from a stationary state and traversing mixed routes containing straight lines and curves at a speed of 0.36km/h to 5.40km/h, the heading angle obtained by the proposed fusion heading measurement method was within 0.5° of the heading angle obtained by the dual-antenna GNSS, indicating that the proposed method was suitable for stable heading acquisition of agricultural machinery in the state of starting up and low-speed movement, which improved the precision and stability of single-antenna agricultural machinery navigation and low-speed driving control and provided technical basis for high-precision agricultural machinery autonomous unmanned operation.