动态限星算法对RTK定位的耗时改进

Improved RTK Positioning Time-Consuming Method Based on Dynamic Satellite-Limited Algorithm

差分卫导实时动态定位(RTK)依靠Kalman滤波功能的实现,当滤波器阶数过高时,会带来计算量的激增,这就会影响定位的耗时。当运算平台能力有限却需要较低的计算时间耗时,动态限星算法能够有效地将RTK的计算耗时降低至合适的耗时需求。运动平台实测结果表明,动态限星算法优化后的RTK定位耗时较优化前减少了50%。

The positioning time-consuming of the Differential Global Navigation Satellite System(DGNSS)Real Time Kinematic(RTK)technology almost depends on the Kalman filter implementation.More filter rank brings bigger computation requirements and more time-consuming.Whereas when small time-consuming is needed and poor workstation setup is existing,dynamic satellite-limited algorithm can effectively reduce time-consuming of RTK to the needed.The results of motion platforms test show that the improved RTK positioning time-consuming is about 2 times less than before.