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The real-tine and accurate knowledge of the operation of an atomic clock is of great significance to satellite navigation and time keeping. In the light of the problems which exist in the real-time solution of the atomic clock operating parameters by means of the standard Kalman filtering, the method for applying the adaptive Kalman filtering model based on the prediction residual to the real-time solution of the clock parameters is proposed. An adaptive factor is constructed by the model based on the standard Kalman filtering model so that the accurate and reliable estimates of the operating parameters may be given rather fast after the frequency modulation or phase modulation of the atomic clock. Finally, in combination with the 3 computational examples of the work on the navigation and time keeping, the effectiveness of the method is verified.

1PPS signal is the standard output of GNSS timing receiver. The pulse is used to synchronize the device to Universal Time Coordinated(UTC) or the GNSS system time, and it is the recovery of GNSS system time or UTC in the local timing receiver. 1PPS signal of GNSS timing receiver is often phase calibrated in discrete steps with an uncorrected frequency error present. If such a calibration was used in GNSS timing receiver, we would observe the 1PPS signal phase error progressing at the uncorrected frequency error. When the phase error grows to the phase step size, a calibration will be done and we will observe a phase step in the 1PPS signal phase. This phase step is GNSS Timing signal granularity. This phenomenon is called the sawtooth behavior of the GNSS 1PPS signal. In order to correct the sawtooth error of 1PPS signal, we study the zoom technique of GNSS timing signal granularity, and propose an improved scheme. The programmable delay line technology is introduced in the improved scheme. The granularity of the programmable delay line device can reach 0.25ns. Combining with the programmable delay line device, we propose a control algorithm which can realize the zoom of local 1PPS signal's granularity. This scheme allows for real-time correction of the quantization error and reduces the residual noise to about 1∼2 nanoseconds peak to peak (pk-pk), and improves the instantaneous and short-term timing accuracy of GNSS 1PPS.

The prediction of the clock errors of atomic clocks plays an important role in the work on time and frequency. Each of the prediction models often used at present has its own merits and shortages. A combination of the predicted results obtained by means of these models can be used to synthesize the characteristics of various kinds of prediction models. In the light of the problem which occurs when the linear combination model is used to make the prediction of clock errors, the concept of learning weight is proposed and the modified combination prediction model is made by taking advantage of various kinds of pieces of accuracy information. For verifying the efficiency of this method the clock error sequences of the IGS (International GNSS Service) of 4 GPS satellites are selected and the predicted results of the quadratic polynomial and grey model are combined. The result shows that the modified model can further improve the stability and accuracy based on the guarantee of the reliability.