Time scale adjusting algorithm based on Kalman filter real-time prediction value

The invention belongs to the field of time frequency and signal processing and provides a time scale adjusting algorithm based on a Kalman filter real-time prediction value. According to a time scale basic equation, the core of the time scale adjusting algorithm is that the weights and prediction values of N clocks can be calculated through (N-1) groups of observed quantities (clock differences). In the prior art, the stability of the time scales is improved by adjusting the weights. According to the algorithm, the time scales are established by adjusting the prediction values in real time, the stability of the time scales is improved, and the continuity of the time scales is guaranteed. According to the technical scheme, the algorithm includes 1, measuring and acquiring (N-1) groups of observed clock differences; 2, utilizing (N-1) independent Kalman filters to perform state estimation on the (N-1) groups of observed clock differences respectively; 3, reconstructing time difference sequences; 4, defining the predicted values; 5, performing real-time prediction value adjustment, and establishing the time scales. Compared with the traditional algorithm, the algorithm has the advantages that the real-time predicable time scales with higher stability and continuity can be established.