电离层异常状态下的自适应平滑滤波算法及性能分析

Analysis on the Performance of the Adaptive Smoothing Filter Algorithm at Ionosphere Anomaly State

卫星导航星基增强和地基增强系统用户终端采用相位平滑伪距的方法,以提高定位精度。通常平滑窗口时间为100 s,这在正常情况下是适合的;但在电离层发生波动情况下,采用这种平滑窗口会使得定位解算结果产生偏差。针对这个问题,采用基于码载偏离度实时估计的方法,自适应确定相位平滑伪距窗口时间,并对该算法的性能进行了计算分析。分析结果表明:基于码载偏离度实时估计的自适应平滑滤波算法能够计算并确定最佳相位平滑时间。该方法相对于传统的100 s平滑时间能够有效提高定位精度,并且避免滤波发散。

Carrier smoothing code algorithm is widely applied in SBAS and GBAS receivers to improve the position accuracy, and the smoothing window was 100 seconds in general. It was a suitable method for most cases, but the position error may be very large at ionosphere anomaly state. This problem was focused and studied in the paper, a new method based on cartier smoothing code real-time estimating at ionosphere anomaly state was introduced, the smoothing window was adaptively estimated, and the performance using the new method was analyzed. The result indicates that the adaptive smoothing filter algorithm can calculate the best smoothing window, improve the position accuracy and avoid the filter divergence.