P-step Kalman-like unbiased FIR algorithm for detecting anomalies of atomic clocks

An extended measurement model anomaly detection algorithm for atomic clocks is proposed based on the p-step Kalman-like iterative Unbiased finite impulse response (UFIR) algorithm. The novel of the proposed algorithm is that it breaks the disadvantage of initializing the noise matrix in the traditional Kalman filter improved algorithms. By accumulating the prediction residuals generated by the process of p-step Kalman-like iterative, the detection statistics are constructed to realize the weaker phase and frequency jump detection of atomic clocks. Simulation results show the effectiveness of the proposed algorithm, and Monte-Carlo (M-C) experiment is used to verify the theoretical calculation of detection probability. We also analyze the measured data of a cesium atomic clock in our timekeeping laboratory, and the results show that the new method is more sensitive to weak frequency jump than the improved algorithm based on the Kalman filter.

Automated summary

An extended measurement model anomaly detection algorithm for atomic clocks is proposed based on the p-step Kalman-like iterative UFIR algorithm, which accumulates prediction residuals to construct detection statistics for the detection of weaker phase and frequency jumps of atomic clocks.