This paper presents technique for qualitative assessment of fatigue crack growth monitoring, utilizing guided elastic waves generated by the sparse PZT piezoelectric transducers network in the pitch – catch configuration. Two Damage Indices (DIs) correlated with the total energy received by a given sensor are used to detect fatigue cracks and monitor their growth. The indices proposed carry marginal signal information content in order to decrease their sensitivity with respect to other undesired non-controllable factors which may distort the received signal. The reason for that is to limit the false calls ratio which besides the damage detection capability of a system, plays a crucial role in applications. However, even such simplified damage indices can alter over a long term, leading to the misclassification problem. Considering a single sensing path, it is very difficult to distinguish whether the resultant change of DIs is caused by a damage or due to decoherence of these DIs. Therefore, assessment approaches based on threshold levels fixed separately for DIs obtained on each of the sensing paths, would eventually lead to a false call. An alternative approach is to compare changes of DIs for all sensing paths. Developing damage distorts the signal only for the sensing paths in its proximity. In order to decrease the misclassification risk, a method of compensating such DIs drift is proposed. The main features and damage detection capabilities of this method will be demonstrated by conducting a laboratory fatigue test of an aircraft panel. The proposed approach has been verified on a real structure during fatigue test of a helicopter tail boom.