Cycle-Slip Detection Methods for Dual-frequency Un-difference Data at Low Elevation Angle

GPS dual-frequency un-difference observations at low elevation angle are prone to large measurement noises, misjudgments, and false negatives in cycle-slip detection. This paper proposes a modified cycle-slip detection algorithm, based on ionosphere residual and MW observation combination. First, the ionosphere residual algorithm is improved by introducing a time window method to calculate a more realistic threshold using the cycle-slip detected error distribution. Then, during wide lane cycle-slip detection, the determinant conditions of the MW combination algorithm was improved by combining the weighted recursive smoothing method and time window method to estimate the wide lane ambiguity and evaluate its precision. Verified by IGS observation data, the improved algorithm achieves good cycle slip detection results.