BDS空间信号异常实时检测与排除方法

Real-time detection and elimination method for BDS signal-in-space anomalies

北斗卫星导航系统(BeiDou navigation satellite system, BDS)空间信号异常是影响其空间信号质量评估的重要因素,检测并排除空间信号异常不仅是构建BDS空间信号故障模型的重要手段,更有利于保障BDS导航定位的完好性.传统基于事后精密星历与广播星历比对的方法存在时延较大、采样率低等问题,本文提出了一种基于Kalman滤波的载波相位平滑伪距算法,并基于BDS空间信号用户测距误差的统计特性建立了实时估计BDS空间信号用户测距误差方法,从而实时检测并排除BDS空间信号异常.基于国际全球导航卫星系统服务(international GNSS service, IGS)地面观测网1 Hz采样率数据的实验结果表明,所提出方法对BDS空间信号用户测距误差的估计精度为1.15 m,可以有效识别由卫星轨道和时钟故障引起的空间信号异常.

The Bei Dou navigation satellite system(BDS) signal-in-space anomaly is an important factor affecting the signal-in-space quality assessment. Detecting and excluding signal-in-space anomalies is not only a method for constructing a BDS signal-in-space fault model but can also help ensure the BDS navigation and positioning integrity. Traditional methods, based on post precision ephemeris and broadcast ephemeris, maintain some disadvantages, such as a large delay and a low sampling rate. In this paper, a carrier-phase smoothing pseudorange algorithm based on Kalman filtering is proposed, and a real-time estimation method of a BDS signal-in-space user range error is established to detect and eliminate signal-in-space anomalies in real time, based on the statistical characteristics of signal-in-space user range error. The experimental results, based on 1 Hz data of the international GNSS service(IGS) ground observation network, show that the proposed method has an estimation accuracy of1.15 m for a BDS signal-in-space user range error, which can effectively identify signal-in-space anomalies caused by satellite orbit and clock faults.