Improving cycle slip detection in ambiguity-fixed precise point positioning for kinematic LEO orbit determination

The global navigation satellite system (GNSS) is a crucial technical tool used for precisely determining the orbit of low earth orbit (LEO) satellites. However, due to the short arc length of spaceborne GNSS observations and the presence of numerous outliers, there is a high rate of misjudgment of cycle slips, which leads to a decrease in orbit determination accuracy. To address this issue, we propose a linear-fit forward and backward moving window averaging (LFBMWA) algorithm and a modified second-order time-difference phase Ionospheric residual (MSTPIR) algorithm to minimize cycle slip misjudgment by suppressing the impact of outliers. Simulation experiments show that the traditional method using FBMWA and STPIR has an 85.53% misjudgment rate, while the proposed method using LFBMWA and MSTPIR reduces it to 13.79%, representing a reduction of over 70 percentage points. Additionally, the proposed method successfully detects all cycle slips. For the GRACE-C and GRACE-D satellites from day 1 to day 250 of 2022, the three-dimensional orbit errors using the proposed method are 3.35 cm and 3.24 cm, respectively, representing a reduction of 30.9% and 32.8% compared to traditional methods. Therefore, the proposed method performs well and can be used as an effective tool for cycle slip detection.