# A Short-Term Forecasting Method of Inter-Frequency Clock Bias for GPS Block IIF Satellites
###### Abstract
The first is parametric estimation on the service side and correction directly in the observation model on the user side [20; 21]. The second is to provide satellite clock products that include a third frequency (L5) [22]. The third is to reduce the weight of third-frequency observations without IFCB correction, and this method can be applied to satellites with small IFCB amplitudes such as the BeiDou system [23]. Considering that the difficulty in satellite clock product estimations and the advantages of multi-frequency observation data, more choices accompany the first processing strategy for IFCB. [PERSON] et al. proposed a method for combining the differences of two different IF combination observations and then estimating the difference epoch by epoch for the above differences [13]. The advantage of this method is that the ambiguity term can be eliminated under no cycle slip, and the common datum bias of each epoch IFCB will be absorbed into the ambiguity parameter. [PERSON] et al. proposed an efficient method derived from the epoch-differenced strategy for fast estimation of IFCBs for Block IIF satellites, and this method can eliminate the receiver terminal clock bias and significantly improves the computational efficiency [20; 21]. [PERSON] et al. proposed a method of estimating the IFCB constant parts and the time-varying parts separately in view of the constant parts of the IFCB having a certain stability in the short term, and the constant part was estimated by three-frequency pseudo-range observations and the time-varying part by three-frequency phase observations. In reality, whichever method is used for IFCB estimation, a large number of global uniformly distributed GNSS continuous tracking stations are required, which is particularly detrimental to multi-frequency real-time PPP and PPP network solutions [24]. Therefore, the main way to handle IFCB is to build forecast models and make direct corrections on the user side. Forecast models of IFCB can be divided into two types. The first one is to study the IFCB time-varying characteristics using the harmonic analysis method and to establish the linear plus periodic model based on the fitting coefficient to implement the IFCB prediction. This approach requires the analysis of the IFCB using long time series. [PERSON] et al. established long-term GPS and BDS IFCB empirical correction models using long-term GNSS observations, and a fourth-order Fourier coefficient fitting model that considered both linearity and periodicity was proposed for IFCB sequences [25]. [PERSON] and [PERSON] established two function models composed of a linear term and a harmonic term with seven orders for MEO satellites and six orders for GEO and IGSO satellites to describe the IFCB variations based on 195 ground tracking stations for a whole year [26]. Another way to establish an IFCB forecast model is to calculate the IFCB correlation for two different time segments and then to extract the IFCB cycle's characteristics and establish the IFCB forecast model based on the correlation coefficient. [PERSON] et al. studied the time-varying characteristic of IFCB based on the correlation analysis using datasets from 129 globally distributed MultiGNSS Experiment (MGEX) stations [14]. For the purpose of forecasting IFCB, the IFCB of the previous day was directly input into the next day in consideration of the periodic changes in the IFCB sequence. The validation results show that all of the prediction models could significantly improve the triple-frequency PPP accuracy. Unfortunately, except for the above IFCB forecasting methods, only a few more effective methods can be used, especially for the establishment of short-term prediction models. Considering the time-varying characteristic of the IFCB and the lag characteristics of the final precision orbit and clock products released by the International GNSS Service (IGS) analysis centers, the epoch-by-epoch sliding Pearson autocorrelation function was used to extract the IFCB periodic features.