We have implemented likelihood testing of the performance of an optimal filter within the online analysis of AURIGA, a sub-Kelvin resonant-bar gravitational wave detector. We demonstrate the effectiveness of this technique in discriminating between impulsive mechanical excitations of the resonant-bar and other spurious excitations. This technique also ensures the accuracy of the estimated parameters such as the signal-to-noise ratio. The efficiency of the technique to deal with non-stationary noise and its application to data from a network of detectors are also discussed
