动态限星算法对RTK定位的耗时改进

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%。

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

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.