In order to improve the sensitivity of time-frequency system integrity monitoring, a time-frequency system integrity monitoring method based on robust Kalman filter was proposed. In this method, a robust Kalman filter model is constructed using the historical measurement data of time difference, the time difference prediction bias and the frequency bias are estimated in real time, and the consistency detection is carried out separately, so that the integrity monitoring is realized. The model and method were verified through measured data and simulation analysis, and the results show that: this method can effectively detect and identify single faults of phase jump and frequency jump, and alarm the user; in a single fault scenario, compared with the traditional integrity monitoring method, the detection sensitivity is increased by about 25.0%; in a multi-fault scenario, the method can effectively detect faults, but there is a problem of insufficient fault identification, and the detection sensitivity is reduced by about 26.1% compared to a single fault, but it is still better than the traditional method.