Characteristics of signal distortion bias and its effect on BDS-3 high-precision baseline solution

Abstract Affected by factors such as satellite navigation signal distortion, non-ideal characteristics of receiver channels, and anti-interference algorithms, the pseudorange observations of BeiDou global navigation satellite system (BDS-3) receivers exhibit signal distortion bias (SDB), which has become a crucial limitation for the processing of BDS high-precision data and services enabled by it. In this paper, without considering the inconsistency in the estimation process for precise products on the operation and control side, we tried to use the SDB estimation method based on the virtual reference receivers from the user side, so as to directly solve the corrections to the SDB between precise products and users’ pseudorange observations, and subsequently make corrections. The characteristics of SDB were systematically evaluated in terms of stability and change trend, and the characteristics of SDB’s impact on the baseline solution and wide-lane ambiguity fixing were theoretically deduced. This proved that such bias can result in errors or failures in double-difference wide-lane ambiguity fixing determined by the Melbourne Wübbena combination, thereby affecting the baseline solution accuracy. Experiments were conducted using observations from eight multi-GNSS experiment (MGEX) stations to evaluate the accuracy of the baseline solution following SDB estimation based on virtual reference stations, and the results indicated that (a) the SDB of BDS-3 satellites at the B1I, B3I, B1C, and B2a frequencies are at the decimeter level and exhibit short-term stability. (b) Incorporating SDB corrections significantly improve the success rates of wide-lane and narrow-lane ambiguity resolution in BDS-3 high-precision baseline solutions. (c) The horizontal and vertical positioning accuracies of the BDS-3 baseline solutions can reach to within 3 mm and 5 mm, respectively. With the application of SDB corrections, the overall positioning accuracy (three-dimensional root mean square, 3D RMS) improves by 16%.