Particle image velocimetry (PIV) measurements are made to investigate the boundary layer developing over a modeled bottom trawl. The random motion of the fishing net structure as well as the flexibility and the porosity of this structure means that it is not enable to access the main characteristics of such a flow, using classical post-processing mathematical tools. An innovative post-treatment tool based on proper orthogonal decomposition (POD) is then developed to extract the mean velocity flow field from each available PIV instantaneous unsteady velocity field. In order to do so, the whole available velocity database is used to compute POD eigenfunctions and the first POD modes are identified as representing the mean flow field. It is then possible to deduce the mean boundary layer flow field for each position of the fishing net structure during PIV measurements. It is then observed that the mean flow field strongly depends on multiple parameters such as surface curvature, structure porosity, random motion of the structure. Streamwise evolution of classical thicknesses of boundary layer flow are also analyzed. The present work also provides benchmark PIV data of the unsteady flow developing on fishing net porous structures, which helps the progress in unsteady numerical codes for this investigation.