Abstract: [Purposes]Satellite clock anomalies are among the critical factors affecting the accuracy and reliability of GNSS precise point positioning (PPP).Conventional detection approaches often rely on prediction models,which suffer from low sensitivity and limited ability to directly mitigate their impact on PPP performance.[Methods]To address this issue,this study proposes a real-time detection method for BDS satellite clock anomalies using multi-station observations.The method incorporates satellite clock bias parameters into an extended PPP model and establishes an anomaly identification and elimination mechanism through combined equation adjustment and residual analysis.[Findings]Experimental results demonstrate that the proposed method can effectively detect anomalies in both simulated and real datasets.The station residual RMS is reduced by 37%and 51.4%,respectively,and the 3D positioning accuracy is improved by up to 42.7% and 62.5%,respectively.Both schemes can achieve a residual RMS of approximately 0.017 m and a 3D positioning accuracy of 0.09 m.[Conclusions]The method significantly strengthens anomaly detection capability and improves PPP accuracy,providing robust support for high-precision applications of the BDS.

Key words: BDS, PPP, station network, satellite clock bias, gross errors detection