Dolphins use their biosonar to discriminate objects with different features through the returning echoes. Cross-modal matching experiments were conducted with a resident bottlenose dolphin (Tursiops aduncus). Four types of objects composed of different materials (water-filled PVC pipes, air-filled PVC pipes, foam ball arrays, and PVC pipes wrapped in closed-cell foam) were used in the experiments, respectively. The size and position of the objects remained the same in each case. The data collected in the experiment showed that the dolphin’s matching accuracy was significantly different across the cases. To gain insight into the underlying mechanism in the experiments, we used finite element methods to construct two-dimensional target detection models of an echolocating dolphin in the vertical plane, based on computed tomography scan data. The acoustic processes of the click’s interaction with the objects and the surrounding media in the four cases were simulated and compared. The simulation results provide some possible explanations for why the dolphin performed differently when discriminating the objects that only differed in material composition in the previous matching experiments.

No abstract

Underwater imaging sonars are widely used for oceanic exploration but are bulky and expensive for some applications. The sonar system of dolphins, which uses sound pulses called clicks to investigate their environment, offers superior shape discrimination capability compared to human-derived imaging sonars of similar size and frequency. In order to gain better understanding of dolphin sonar imaging, we train a dolphin to acoustically interrogate certain objects and match them visually. We record the echoes the dolphin receives and are able to extract object shape information from these recordings. We find that infusing prior information into the processing, specifically the sparsity of the shapes, yields a clearer interpretation of the echoes than conventional signal processing. We subsequently develop a biomimetic sonar system that combines sparsity-aware signal processing with high-frequency broadband click signals similar to that of dolphins, emitted by an array of transmitters. Our findings offer insights and tools towards compact higher resolution sonar imaging technologies.

Dolphins and porpoises use their sophisticated biosonar systems for targets detection, within a range of a few meters to about 200 m, there is not a better sonar on the planet. In this study, the high resolution computer tomography (CT) scan data were used to create the detecting click signal propagation models of Atlantic bottlenose dolphins (Tursiops truncatus) and harbor porpoise (Phocoena phocoena). The finite element methods (FEM) were used to simulate the processes of the clicks emitted from phonic lips and transmit to the water through animals’ heads. The biosonar beam forming in the nearfield and farfield including the amplitude contours were determined and compared to the prior measurement results. There were no evidences of convergence in the farfield, which were consistent with measurement results for Tursiops truncatus. Additionally, in a cross-modal matching experiments with Tursiops, we found that the accuracy of the successive match was significantly different when the following subjects with same shape were used (water-filled PVC pipes, air-filled PVC pipes, foam ball array, and PVC pipes wrapped by foam) the results of FE model shed some light on the reasons why the animal has significant difference in performances when detecting different targets in the experiments.