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The goal of the timekeeping system is to establish and maintain a stable and reliable time scale. The time scale algorithm is based on this goal to calculate a time scale with higher frequency stability, accuracy and reliability. The essence of the time scale algorithm is to integrate the primary clocks in the timekeeping system, and estimate the weight and predicted value of N atomic clocks through the N-1 group of observation clock differences between each atomic clock and the main clock. The traditional weighted average algorithm will ignore the noise process that plays a major role, and pay more attention to the reasonable distribution of weights to improve the stability of the synthetic atomic time. It lacks attention to noise. Aiming at the real-time requirements of the time-keeping system, the atomic clock noise model is studied, and the application of Kalman filter and frequency jump detection is studied in the frequency prediction process, and compared with the traditional weighted average algorithm, The simulation results show that the improved algorithm improves the stability and reliability of the synthetic atomic time in the medium and long term. It not only retains the good characteristics of continuous and real-time AT1 time scale, but also avoids the problem of divergence of Kalman algorithm. After practical testing, it can be applied to the system construction of small time-keeping laboratories.