Seafloor characterisation using multibeam sonar echo signal processing and image analysis

The authors propose the approach to multibeam seafloor characterisation which relies on the combined, concurrent use of two different techniques of multibeam sonar data processing. The first one is based on constructing the grey-level sonar images of seabed using the echoes received in the consecutive beams. Then, the parameters describing the local region of sonar image, namely, the local standard deviation of a grey level, and the slope of a local autocorrelation function of a grey level, are calculated. The second technique assumes the use of a set of parameters of the multibeam echo envelope, similarly as in single beam classification. For selected parameters, namely, for echo envelope moment of inertia and for echo envelope fractal dimension, the slope of their angular dependence is calculated. Finally, the quantities obtained by these 2 techniques have been combined together and the multidimensional distributions of sets of them have been analysed in the context of seabed classification procedure. The approach has been tested using multibeam data records acquired from several bottom types in the Gulf of Gdańsk region. The preliminary results show that application of the proposed combined approach should improve the classification performance in comparison with that of using only the one scheme of seafloor multibeam data processing.