Estimating the Allan Variance from Frequency Measurements with Missing Data

The Allan variance is the key measure for stability analysis, a fundamental tool to establish the performances of atomic clocks, which are often critical elements in many applications, such as global navigation satellite systems (GNSS). In some applications, only frequency measurements with numerous missing data are available. Because of missing data, the resulting Allan variance can be dramatically different from the expected stability behavior. We have developed an Allan variance estimator which corrects this divergence. We show the effectiveness of our estimator by applying it to frequency measurements with up to 94.4% of missing data.