Nowadays, hearing aids have efficient signal processing options to improve speech intelligibility in noise. This work concerns the characterization of the microphone systems directivity available in hearing aids. In recent decades, "adaptive" directivities have been implemented in hearing aids, thus making it possible to focus on useful sound sources in the hearing aid patient environment. These options use the principles of sound environments detection, acoustic beamforming and noise reduction. Performances of these options can be estimated with subjective methods (as speech audiometry in noise), and objective methods (listening effort, intelligibility indicators as HASPI, SII, STI, etc.). But these methods provide an overall assessment of all the processing involved in speech enhancement and are not designed to characterize the effects of adaptive directivity. We developed an experimental technique based on sound sources separation with phase opposition diffusion (known as "Hagerman" method) to draw polar diagrams of adaptive directivity, for realistic sound environments. We used a sound multi-diffusion system to generate various sound environments with noise and speech sources around an artificial head equipped with hearing aids. The first results show the adaptive directivity effects associated with noise reduction provided by the latest hearing aids generation on everyday hearing scenes.