A data fusion technique implementing the principles of acoustic emission (AE), ultrasonic testing (UT) and digital image correlation (DIC) was employed to in situ monitor crack propagation in an Al 2024 alloy compact tension (CT) specimen. The specimen was designed according to ASTM E647-08 and was pre-cracked under fatigue loading to ensure stable crack growth. Tensile (Mode I) loads were applied according to ASTM E1290-08 while simultaneously recording AE activity, transmitting ultrasonic pulses and measuring full-field surface strains. Realtime 2D source location AE algorithms and visualization provided by the DIC system allowed the full quantification of the crack growth and the cross-validation of the recorded non-destructive testing data. In post mortem, waveform features sensitive to crack propagation were extracted and visible trends as a function of computed crack length were observed. In addition, following a data fusion approach, features from the three independent monitoring systems were combined to define damage sensitive correlations. Furthermore a novelty detector based on the Mahalanobis outlier analysis was implemented to quantify the extent of crack growth and to define a more robust sensing basis for the proposed system.