GPS/BDS triple-frequency cycle slip detection and repair algorithm based on adaptive detection threshold and FNN-derived ionospheric delay compensation

Abstract

A refined triple-frequency cycle slip detection and repair algorithm for GPS/BDS undifferenced observables under high ionospheric disturbances is proposed. In this method, three linearindependent optimal observables combinations for GPS/BDS are selected. The residual ionospheric delay estimated from a “calculation-prediction mechanism”, namely flexibly determine whether to calculate delay by observables themselves or to predict delay by a feedforward neural network (FNN), is used to compensate for the detection values. Additionally, we devise an adaptive detection threshold based on actual noise level to detect the cycle slip, and adopt the modified least-square decorrelation adjustment (MLAMBDA) to fix integer cycle slip. The performance of the proposed algorithm was tested with observables at 30 s sampling rate in a 2-day geomagnetic storm period. Results showed that the proposed algorithm can detect and repair all kinds of cycle slips as small as one cycle in the case of high ionospheric disturbances. No false repairs are generated despite the occurrence of very few misjudgments. ARTICLE INFO Article history: Received 7 December 2019 Accepted 4 February 2020 Available online 16 April 2020