摘要
该文提出了一个实时拖拉机位置确定系统 ,该系统由一个六轴惯性测量单元 (IMU )和一个 Garm in全球定位系统(GPS)组成。在系统中 ,设计了一个 Kalm an过滤器来综合两个传感器的信号 ,以滤去 GPS信号中的噪音 ,融合冗余信息 ,最后得到一个有较高更新速度的输出信号。此外该系统还能够补偿 IMU的偏移误差。通过使用该系统 ,低价的 GPS可以替代高价的 GPS,并且保持良好的精确性。试验和融合结果表明该系统确定的拖拉机位置误差比单一使用 GPS的系统的误差要大大减小 :当拖拉机速度约为 1.3 4m /s时 ,该系统东向轴的平均偏差为 0 .48m ,而 GPS的平均偏差为 1.2 8m ;北向轴的偏差从 1.48m降为 0 .3 2 m。系统的更新频率则从原有 GPS的 1Hz增加到
A real time tractor position estimation system, which consists of a six axis inertial measurement unit (IMU) and a Garmin global positioning system (GPS) was developed. A Kalman filter was designed to integrate the signals from both sensors so that the noise in GPS signal was smoothed out, the redundant information fused and a high update rate of output signals obtained. The drift error of IMU was also compensated. By using this system, a low cost GPS can be used to replace expensive one with a high accuracy. Test and fusion results showed that the positioning error of the tractor estimated using this system was greatly reduced from a GPS only system. At a tractor speed of about 1.34 m/s, the mean bias in easting axis of the system was 0.48 m, comparing to the GPS mean bias of 1.28 m, and the mean bias in northing axis was reduced from 1.48 m to 0.32 m. The update frequency of the GPS system was increased from 1 to 9 Hz.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2002年第5期96-101,共6页
Transactions of the Chinese Society of Agricultural Engineering
基金
Illinois Council on Food and Agricultural Research,the Strategic Research Initiative Program in Information Systems andTechnology (CFAR- SRI- IT) and USDA Hatch Funds
